MMTU-benchmark/MMTU huggingface dataset:
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A   | B     | C     | D    | E   | F   | G      | H     | I    | J   | K             | L   | M   | N      | O     | P    | Q   | R   |
|---:|:----|:------|:------|:-----|:----|:----|:-------|:------|:-----|:----|:--------------|:----|:----|:-------|:------|:-----|:----|:----|
| 26 | 23  | 17    | 544   | 220  |     | 23  | 17     | 544   | 220  |     | 0             |     | 23  | 17     | 544   | 220  |     | 0.0 |
| 27 | 24  | 18    | 1024  | 400  |     | 24  | 18     | 1024  | 400  |     | 0             |     | 24  | 18     | 1024  | 400  |     | 0.0 |
| 28 | 25  | 19    | 32801 | 8021 |     | 25  | 19     | 32801 | 8021 |     | 0             |     | 25  | 19     | 32801 | 8021 |     | 0.0 |
| 29 | 26  | 1A    | 0     | 0    |     | 26  | 1A     | 0     | 0    |     | 0             |     | 26  | 1A     | 0     | 0    |     | 0.0 |
| 30 | 27  | 1B    | 125   | 7D   |     | 27  | 1B     | 125   | 7D   |     | 0             |     | 27  | 1B     | 125   | 7D   |     | 0.0 |
| 31 | 28  | 1C    | 1518  | 5EE  |     | 28  | 1C     | 1518  | 5EE  |     | 0             |     | 28  | 1C     | 1518  | 5EE  |     | 0.0 |
| 32 | 29  | 1D    | 0     | 0    |     | 29  | 1D     | 0     | 0    |     | 0             |     | 29  | 1D     | 0     | 0    |     | 0.0 |
| 33 | 30  | 1E    | 2     | 2    |     | 30  | 1E     | 2     | 2    |     | 0             |     | 30  | 1E     | 2     | 2    |     | 0.0 |
| 34 | 31  | 1F    | 0     | 0    |     | 31  | 1F     | 0     | 0    |     | 0             |     | 31  | 1F     | 0     | 0    |     | 0.0 |
| 35 |     |       |       |      |     |     |        |       |      |     |               |     |     |        |       |      |     |     |
| 36 |     | 0x467 | 8193  | 8FCC |     |     | 0x0467 | 8193  | 2001 |     | [Target Cell] |     |     | 0x0467 | 8193  | 2001 |     | 0.0 |
| 37 |     | 0x468 | 0     | 2001 |     |     | 0x0468 | 0     | 0    |     | 0             |     |     | 0x0468 | 0     | 0    |     | 0.0 |



min_row: 26
max_row: 37
min_col: 1
max_col: 18
target_cell_row_idx: 36
target_cell_col_idx: 11
target_cell_value: 0
formula: =C36-H36
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  1 | 16             | bits                                                              |
|  2 | [Target Cell]  | steps                                                             |
|  3 | 2048           | +-range (mV)                                                      |
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |



min_row: 1
max_row: 12
min_col: 1
max_col: 2
target_cell_row_idx: 2
target_cell_col_idx: 1
target_cell_value: 65535
formula: =2^A1-1
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  1 | 16             | bits                                                              |
|  2 | 65535          | steps                                                             |
|  3 | 2048           | +-range (mV)                                                      |
|  4 | [Target Cell]  | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |
| 13 | 2              | 0.1250038148137                                                   |
| 14 | 3              | 0.1875057222205                                                   |



min_row: 1
max_row: 14
min_col: 1
max_col: 2
target_cell_row_idx: 4
target_cell_col_idx: 1
target_cell_value: 4096
formula: =2*A3
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  1 | 16             | bits                                                              |
|  2 | 65535          | steps                                                             |
|  3 | 2048           | +-range (mV)                                                      |
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | [Target Cell]                                                     |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |
| 13 | 2              | 0.1250038148137                                                   |
| 14 | 3              | 0.1875057222205                                                   |
| 15 |                |                                                                   |
| 16 |                | difference between the read values and its equivalent LSB         |
| 17 | 1              | -9.53717931448383e-07                                             |



min_row: 1
max_row: 17
min_col: 1
max_col: 2
target_cell_row_idx: 7
target_cell_col_idx: 2
target_cell_value: 0.0625009536888685
formula: =A4/A2
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  2 | 65535          | steps                                                             |
|  3 | 2048           | +-range (mV)                                                      |
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | [Target Cell]                                                     |
| 13 | 2              | 0.1250038148137                                                   |
| 14 | 3              | 0.1875057222205                                                   |
| 15 |                |                                                                   |
| 16 |                | difference between the read values and its equivalent LSB         |
| 17 | 1              | -9.53717931448383e-07                                             |
| 18 | 2              | -1.90743596290011e-06                                             |
| 19 | 3              | -2.86115389447339e-06                                             |



min_row: 2
max_row: 19
min_col: 1
max_col: 2
target_cell_row_idx: 12
target_cell_col_idx: 2
target_cell_value: 0.0625019074068
formula: =1000*0.0000625019074068
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  1 | 16             | bits                                                              |
|  2 | 65535          | steps                                                             |
|  3 | 2048           | +-range (mV)                                                      |
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | [Target Cell]                                                     |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |
| 13 | 2              | 0.1250038148137                                                   |
| 14 | 3              | 0.1875057222205                                                   |
| 15 |                |                                                                   |
| 16 |                | difference between the read values and its equivalent LSB         |
| 17 | 1              | -9.53717931448383e-07                                             |
| 18 | 2              | -1.90743596290011e-06                                             |



min_row: 1
max_row: 18
min_col: 1
max_col: 2
target_cell_row_idx: 8
target_cell_col_idx: 2
target_cell_value: 0.125001907377737
formula: =A8*$B$7
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A   | B                                                                 |
|---:|:----|:------------------------------------------------------------------|
|  7 | 1.0 | 0.0625009536888685                                                |
|  8 | 2.0 | 0.125001907377737                                                 |
|  9 | 3.0 | 0.187502861066606                                                 |
| 10 |     |                                                                   |
| 11 |     | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1.0 | 0.0625019074068                                                   |
| 13 | 2.0 | 0.1250038148137                                                   |
| 14 | 3.0 | 0.1875057222205                                                   |
| 15 |     |                                                                   |
| 16 |     | difference between the read values and its equivalent LSB         |
| 17 | 1.0 | [Target Cell]                                                     |
| 18 | 2.0 | -1.90743596290011e-06                                             |
| 19 | 3.0 | -2.86115389447339e-06                                             |



min_row: 7
max_row: 19
min_col: 1
max_col: 2
target_cell_row_idx: 17
target_cell_col_idx: 2
target_cell_value: -9.53717931448383e-07
formula: =B7-B12
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |
| 13 | 2              | 0.1250038148137                                                   |
| 14 | 3              | [Target Cell]                                                     |
| 15 |                |                                                                   |
| 16 |                | difference between the read values and its equivalent LSB         |
| 17 | 1              | -9.53717931448383e-07                                             |
| 18 | 2              | -1.90743596290011e-06                                             |
| 19 | 3              | -2.86115389447339e-06                                             |



min_row: 4
max_row: 19
min_col: 1
max_col: 2
target_cell_row_idx: 14
target_cell_col_idx: 2
target_cell_value: 0.1875057222205
formula: =1000*0.0001875057222205
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A            | B                  | C             | D                  | E               | F   | G       | H           | I          |
|---:|:-------------|:-------------------|:--------------|:-------------------|:----------------|:----|:--------|:------------|:-----------|
|  1 | Elapsed Time | SOC Unfiltered (%) | Voltage (V)   | Nom Avail Cap (Ah) | Avg Current (A) |     | Voltage | NomAvailCap | AvgCurrent |
|  2 | 00:00:00     | 10                 | [Target Cell] | 0.848              | -0.142          |     | 3373    | 848         | -142       |
|  3 | 00:00:04     | 10                 | 3.373         | 0.848              | -0.142          |     | 3373    | 848         | -142       |
|  4 | 00:00:08     | 10                 | 3.372         | 0.848              | -0.123          |     | 3372    | 848         | -123       |
|  5 | 00:00:12     | 10                 | 3.373         | 0.847              | -0.125          |     | 3373    | 847         | -125       |
|  6 | 00:00:16     | 10                 | 3.352         | 0.847              | -0.141          |     | 3352    | 847         | -141       |
|  7 | 00:00:20     | 10                 | 3.373         | 0.847              | -0.143          |     | 3373    | 847         | -143       |
|  8 | 00:00:24     | 10                 | 3.373         | 0.847              | -0.12           |     | 3373    | 847         | -120       |
|  9 | 00:00:28     | 10                 | 3.373         | 0.847              | -0.128          |     | 3373    | 847         | -128       |
| 10 | 00:00:32     | 10                 | 3.371         | 0.847              | -0.133          |     | 3371    | 847         | -133       |
| 11 | 00:00:36     | 10                 | 3.373         | 0.847              | -0.122          |     | 3373    | 847         | -122       |
| 12 | 00:00:40     | 10                 | 3.371         | 0.846              | -0.128          |     | 3371    | 846         | -128       |



min_row: 1
max_row: 12
min_col: 1
max_col: 9
target_cell_row_idx: 2
target_cell_col_idx: 3
target_cell_value: 3.373
formula: =G2/1000
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                             | B                  | C   |
|---:|:------------------------------|:-------------------|:----|
|  2 |                               |                    |     |
|  3 | V1+ =                         | 9                  | V   |
|  4 | Vs+ =                         | 0.4                | V   |
|  5 | V1- =                         | 3                  | V   |
|  6 | Vs- =                         | 0.3945             | V   |
|  7 | V2 =                          | 5                  | V   |
|  8 | Rh =                          | 1000000            | Ω   |
|  9 | Rp <<  Rh                     | 10000              | Ω   |
| 10 |                               |                    |     |
| 11 |                               |                    |     |
| 12 | R1 =                          | [Target Cell]      | Ω   |
| 13 | R2 =                          | 58386.85573474539  | Ω   |
| 14 |                               |                    |     |
| 15 | Want this number less than 7V |                    |     |
| 16 | Max Vs  =                     | 1.8767066324437727 | V   |



min_row: 2
max_row: 16
min_col: 1
max_col: 3
target_cell_row_idx: 12
target_cell_col_idx: 2
target_cell_value: 1186066.693378924
formula: =(B4*(B5-B6)-B6*(B3-B4))/(-B4*((B7-B6)/(B8+B9))-(B6*(B4/B8)))
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A              | B                                                                 |
|---:|:---------------|:------------------------------------------------------------------|
|  3 | 2048           | +-range (mV)                                                      |
|  4 | 4096           | range (mV)                                                        |
|  5 |                |                                                                   |
|  6 | number of LSBs | Equivalent in (mV)                                                |
|  7 | 1              | 0.0625009536888685                                                |
|  8 | 2              | 0.125001907377737                                                 |
|  9 | 3              | 0.187502861066606                                                 |
| 10 |                |                                                                   |
| 11 |                | values read by program (in mV) when measuring GND in channel zero |
| 12 | 1              | 0.0625019074068                                                   |
| 13 | 2              | [Target Cell]                                                     |
| 14 | 3              | 0.1875057222205                                                   |
| 15 |                |                                                                   |
| 16 |                | difference between the read values and its equivalent LSB         |
| 17 | 1              | -9.53717931448383e-07                                             |
| 18 | 2              | -1.90743596290011e-06                                             |
| 19 | 3              | -2.86115389447339e-06                                             |



min_row: 3
max_row: 19
min_col: 1
max_col: 2
target_cell_row_idx: 13
target_cell_col_idx: 2
target_cell_value: 0.1250038148137
formula: =1000*0.0001250038148137
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                             | B                  | C   |
|---:|:------------------------------|:-------------------|:----|
|  3 | V1+ =                         | 9                  | V   |
|  4 | Vs+ =                         | 0.4                | V   |
|  5 | V1- =                         | 3                  | V   |
|  6 | Vs- =                         | 0.3945             | V   |
|  7 | V2 =                          | 5                  | V   |
|  8 | Rh =                          | 1000000            | Ω   |
|  9 | Rp <<  Rh                     | 10000              | Ω   |
| 10 |                               |                    |     |
| 11 |                               |                    |     |
| 12 | R1 =                          | 1186066.693378924  | Ω   |
| 13 | R2 =                          | [Target Cell]      | Ω   |
| 14 |                               |                    |     |
| 15 | Want this number less than 7V |                    |     |
| 16 | Max Vs  =                     | 1.8767066324437727 | V   |



min_row: 3
max_row: 16
min_col: 1
max_col: 3
target_cell_row_idx: 13
target_cell_col_idx: 2
target_cell_value: 58386.85573474539
formula: =B4/(((B3-B4)/B12)-(B4/B8))
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A           | B             |   C |   D |   E |   F |   G |   H |   I |   J |   K |   L |
|---:|:------------|:--------------|----:|----:|----:|----:|----:|----:|----:|----:|----:|----:|
|  1 | Hexadecimal | 80            |  80 |  80 |  81 |  81 |  82 |  82 |  83 |  83 |  84 |  84 |
|  2 | Decimal     | [Target Cell] | 128 | 128 | 129 | 129 | 130 | 130 | 131 | 131 | 132 | 132 |
|  3 | Time        | 1             |   2 |   3 |   4 |   5 |   6 |   7 |   8 |   9 |  10 |  11 |



min_row: 1
max_row: 3
min_col: 1
max_col: 12
target_cell_row_idx: 2
target_cell_col_idx: 2
target_cell_value: 128
formula: =HEX2DEC(B1)
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A   | B   | C   | D   | E                       | F   | G                      |
|---:|:----|:----|:----|:----|:------------------------|:----|:-----------------------|
|  3 |     |     |     |     | Max Voltage calculation |     |                        |
|  4 |     |     |     |     |                         |     |                        |
|  5 |     |     |     |     | 5.8                     | V   | VZEN                   |
|  6 |     |     |     |     | 15000                   | Ohm | RUVLO2                 |
|  7 |     |     |     |     | 10000                   | Ohm | Internal Resistor      |
|  8 |     |     |     |     | 84000                   | Ohm | RUVLO1                 |
|  9 |     |     |     |     |                         |     |                        |
| 10 |     |     |     |     | 0.0001                  | A   | EN pin current         |
| 11 |     |     |     |     | 0.0004533333333333333   | A   | RENB current           |
| 12 |     |     |     |     |                         |     |                        |
| 13 |     |     |     |     | [Target Cell]           | V   | VEN max                |
| 14 |     |     |     |     | 53.279999999999994      | V   | Max Voltage marked VIN |



min_row: 3
max_row: 14
min_col: 1
max_col: 7
target_cell_row_idx: 13
target_cell_col_idx: 5
target_cell_value: 6.8
formula: =E5+E7*E10
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                             | B                 | C   |
|---:|:------------------------------|:------------------|:----|
|  6 | Vs- =                         | 0.3945            | V   |
|  7 | V2 =                          | 5                 | V   |
|  8 | Rh =                          | 1000000           | Ω   |
|  9 | Rp <<  Rh                     | 10000             | Ω   |
| 10 |                               |                   |     |
| 11 |                               |                   |     |
| 12 | R1 =                          | 1186066.693378924 | Ω   |
| 13 | R2 =                          | 58386.85573474539 | Ω   |
| 14 |                               |                   |     |
| 15 | Want this number less than 7V |                   |     |
| 16 | Max Vs  =                     | [Target Cell]     | V   |



min_row: 6
max_row: 16
min_col: 1
max_col: 3
target_cell_row_idx: 16
target_cell_col_idx: 2
target_cell_value: 1.8767066324437727
formula: =40*B13/(B12+B13)
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                     | B           | C                  | D              | E   |
|---:|:----------------------|:------------|:-------------------|:---------------|:----|
|  6 | [Channel Information] |             | AINCOM             | Level Shift ON |     |
|  7 | Channel Name          | ADC1        | Data Rate          | 20sps          |     |
|  8 | Sampling Frequency    | 4.999       |                    |                |     |
|  9 | Input Frequency       | 0           |                    |                |     |
| 10 | Max Code              | 2147483647  |                    |                |     |
| 11 | Max Voltage           | 2.5         |                    |                |     |
| 12 | Min Code              | -2147483648 |                    |                |     |
| 13 | Min Voltage           | -2.5        |                    |                |     |
| 14 | Data Format           | Decimal     |                    |                |     |
| 15 | [Channel Data]        |             |                    |                |     |
| 16 |                       | 498         | Standard Deviation | [Target Cell]  |     |
| 17 |                       | 382         | Highest Value      | 932            |     |
| 18 |                       | 719         | Lowest Value       | -671           |     |
| 19 |                       | 280         |                    |                |     |
| 20 |                       | -19         |                    |                |     |
| 21 |                       | 384         |                    |                |     |
| 22 |                       | 257         |                    |                |     |
| 23 |                       | 153         |                    |                |     |
| 24 |                       | -123        |                    |                |     |
| 25 |                       | -267        |                    |                |     |
| 26 |                       | 257         |                    |                |     |



min_row: 6
max_row: 26
min_col: 1
max_col: 5
target_cell_row_idx: 16
target_cell_col_idx: 4
target_cell_value: 237.10705438966195
formula: =STDEV(B16:B2199)
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A   | B   | C   | D   | E                     | F   | G                      |
|---:|:----|:----|:----|:----|:----------------------|:----|:-----------------------|
|  4 |     |     |     |     |                       |     |                        |
|  5 |     |     |     |     | 5.8                   | V   | VZEN                   |
|  6 |     |     |     |     | 15000                 | Ohm | RUVLO2                 |
|  7 |     |     |     |     | 10000                 | Ohm | Internal Resistor      |
|  8 |     |     |     |     | 84000                 | Ohm | RUVLO1                 |
|  9 |     |     |     |     |                       |     |                        |
| 10 |     |     |     |     | 0.0001                | A   | EN pin current         |
| 11 |     |     |     |     | 0.0004533333333333333 | A   | RENB current           |
| 12 |     |     |     |     |                       |     |                        |
| 13 |     |     |     |     | 6.8                   | V   | VEN max                |
| 14 |     |     |     |     | [Target Cell]         | V   | Max Voltage marked VIN |



min_row: 4
max_row: 14
min_col: 1
max_col: 7
target_cell_row_idx: 14
target_cell_col_idx: 5
target_cell_value: 53.279999999999994
formula: =(E10+E11)*E8+E13
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                     | B           | C                  | D              | E   |
|---:|:----------------------|:------------|:-------------------|:---------------|:----|
|  6 | [Channel Information] |             | AINCOM             | Level Shift ON |     |
|  7 | Channel Name          | ADC1        | Data Rate          | 20sps          |     |
|  8 | Sampling Frequency    | 4.999       |                    |                |     |
|  9 | Input Frequency       | 0           |                    |                |     |
| 10 | Max Code              | 2147483647  |                    |                |     |
| 11 | Max Voltage           | 1.25        |                    |                |     |
| 12 | Min Code              | -2147483648 |                    |                |     |
| 13 | Min Voltage           | -1.25       |                    |                |     |
| 14 | Data Format           | Decimal     |                    |                |     |
| 15 | [Channel Data]        |             |                    |                |     |
| 16 |                       | 179         | Standard Deviation | [Target Cell]  |     |
| 17 |                       | 445         | Highest Value      | 1181           |     |
| 18 |                       | 404         | Lowest Value       | -411           |     |
| 19 |                       | 517         |                    |                |     |
| 20 |                       | 637         |                    |                |     |
| 21 |                       | 491         |                    |                |     |
| 22 |                       | 131         |                    |                |     |
| 23 |                       | -6          |                    |                |     |
| 24 |                       | 177         |                    |                |     |
| 25 |                       | 314         |                    |                |     |
| 26 |                       | 41          |                    |                |     |



min_row: 6
max_row: 26
min_col: 1
max_col: 5
target_cell_row_idx: 16
target_cell_col_idx: 4
target_cell_value: 248.37122605126103
formula: =STDEV(B16:B2199)