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                  |
|---:|:----------|:-----------|:-------------|:----|:----------|:---------|:--------------|:-------------------|:-------------------|
|  1 | Name      | Node Count | Routed (mil) |     |           | Min      | Max           | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | 777.155  | 1433.515      | 328.18000000000006 | 1354.7073846153849 |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | 777.155  | [Target Cell] | 31.86650000000003  | 809.0215000000001  |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |          |               |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024  | 1149.891      | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477 | 1149.891      | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |          |               |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667  | 1103.03       | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667  | 830.358       | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |          |               |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |          |               |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |          |               |                    |                    |
| 13 | DDR_A9    | 2          | 1419.369     |     |           |          |               |                    |                    |



min_row: 1
max_row: 13
min_col: 1
max_col: 9
target_cell_row_idx: 3
target_cell_col_idx: 7
target_cell_value: 840.888
formula: =MAX(C2:C3)
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   |
|---:|:----|:--------------------|:-------------------|:----|
|  6 |     | Ven (V)             | 1.25               |     |
|  7 |     | Ip (A)              | 1e-06              |     |
|  8 |     | Ih (A)              | 3e-06              |     |
|  9 |     | vinstart (V)        | 6.5                |     |
| 10 |     | vinstop (V)         | 6                  |     |
| 11 |     | R1 (kOhm)           | 166.66666666666666 |     |
| 12 |     | R2 (kOhm)           | 38.46153846153847  |     |
| 13 |     | R1_actual (kOhm)    | 165                |     |
| 14 |     | R2_actual (kOhm)    | 38.3               |     |
| 15 |     | vinstart_actual (V) | 6.470117493472586  |     |
| 16 |     | vinstop_actual (V)  | [Target Cell]      |     |
| 17 |     |                     |                    |     |
| 18 |     |                     |                    |     |
| 19 |     |                     |                    |     |
| 20 |     |                     |                    |     |
| 21 |     |                     |                    |     |
| 22 |     |                     |                    |     |
| 23 |     |                     |                    |     |
| 24 |     |                     |                    |     |
| 25 |     |                     |                    |     |



min_row: 6
max_row: 25
min_col: 1
max_col: 4
target_cell_row_idx: 16
target_cell_col_idx: 3
target_cell_value: 5.9751174934725855
formula: =C15-1000*C13*C8
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   |
|---:|:----|:--------------------|:-------------------|:----|
|  5 |     |                     |                    |     |
|  6 |     | Ven (V)             | 1.25               |     |
|  7 |     | Ip (A)              | 1e-06              |     |
|  8 |     | Ih (A)              | 3e-06              |     |
|  9 |     | vinstart (V)        | 6.5                |     |
| 10 |     | vinstop (V)         | 6                  |     |
| 11 |     | R1 (kOhm)           | 166.66666666666666 |     |
| 12 |     | R2 (kOhm)           | 38.46153846153847  |     |
| 13 |     | R1_actual (kOhm)    | 165                |     |
| 14 |     | R2_actual (kOhm)    | 38.3               |     |
| 15 |     | vinstart_actual (V) | [Target Cell]      |     |
| 16 |     | vinstop_actual (V)  | 5.9751174934725855 |     |
| 17 |     |                     |                    |     |
| 18 |     |                     |                    |     |
| 19 |     |                     |                    |     |
| 20 |     |                     |                    |     |
| 21 |     |                     |                    |     |
| 22 |     |                     |                    |     |
| 23 |     |                     |                    |     |
| 24 |     |                     |                    |     |
| 25 |     |                     |                    |     |



min_row: 5
max_row: 25
min_col: 1
max_col: 4
target_cell_row_idx: 15
target_cell_col_idx: 3
target_cell_value: 6.470117493472586
formula: =C6*(C13/C14+1)-1000*C13*C7
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:
|    | D        | E       | F         | G         | H        | I        | J    | K          | L          | M        | N             |
|---:|:---------|:--------|:----------|:----------|:---------|:---------|:-----|:-----------|:-----------|:---------|:--------------|
|  1 | CC3200   |         |           |           |          |          |      |            |            |          |               |
|  2 | Prev Cnt | New Cnt | Python Rx | CC3200 Rx | Python % | CC3200 % | Bias | CC3200 Win | Python Win | Tie 100% | Tie Other     |
|  3 | 362      | 367     | 1         | 5         | 0.2      | 1        | 4    | 1          |            |          | [Target Cell] |
|  4 | 367      | 372     | 5         | 5         | 1        | 1        | 0    |            |            | 1        |               |
|  5 | 372      | 377     | 2         | 5         | 0.4      | 1        | 3    | 1          |            |          |               |
|  6 | 377      | 381     | 4         | 4         | 0.8      | 0.8      | 0    |            |            |          | 1             |
|  7 | 381      | 386     | 5         | 5         | 1        | 1        | 0    |            |            | 1        |               |
|  8 | 386      | 391     | 5         | 5         | 1        | 1        | 0    |            |            | 1        |               |
|  9 | 391      | 394     | 3         | 3         | 0.6      | 0.6      | 0    |            |            |          | 1             |
| 10 | 394      | 398     | 1         | 4         | 0.2      | 0.8      | 3    | 1          |            |          |               |
| 11 | 398      | 403     | 3         | 5         | 0.6      | 1        | 2    | 1          |            |          |               |
| 12 | 403      | 404     | 1         | 1         | 0.2      | 0.2      | 0    |            |            |          | 1             |
| 13 | 404      | 409     | 4         | 5         | 0.8      | 1        | 1    | 1          |            |          |               |



min_row: 1
max_row: 13
min_col: 4
max_col: 14
target_cell_row_idx: 3
target_cell_col_idx: 14
target_cell_value: None
formula: =IF(AND(J3=0,I3<>1),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          | C            | D   | E         | F             | G        | H                  | I                  |
|---:|:----------|:-----------|:-------------|:----|:----------|:--------------|:---------|:-------------------|:-------------------|
|  1 | Name      | Node Count | Routed (mil) |     |           | Min           | Max      | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | [Target Cell] | 1433.515 | 328.18000000000006 | 1354.7073846153849 |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | 777.155       | 840.888  | 31.86650000000003  | 809.0215000000001  |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |               |          |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024       | 1149.891 | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477      | 1149.891 | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |               |          |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667       | 1103.03  | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667       | 830.358  | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |               |          |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |               |          |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |               |          |                    |                    |



min_row: 1
max_row: 12
min_col: 1
max_col: 9
target_cell_row_idx: 2
target_cell_col_idx: 6
target_cell_value: 777.155
formula: =MIN(C2:C3)
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 | Name      | Node Count | Routed (mil) |     |           | Min      | Max      | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | 777.155  | 1433.515 | 328.18000000000006 | [Target Cell]      |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | 777.155  | 840.888  | 31.86650000000003  | 809.0215000000001  |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |          |          |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024  | 1149.891 | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477 | 1149.891 | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |          |          |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667  | 1103.03  | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667  | 830.358  | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |          |          |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |          |          |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |          |          |                    |                    |



min_row: 1
max_row: 12
min_col: 1
max_col: 9
target_cell_row_idx: 2
target_cell_col_idx: 9
target_cell_value: 1354.7073846153849
formula: =AVERAGE(C2:C27)
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 | Name      | Node Count | Routed (mil) |     |           | Min           | Max      | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | 777.155       | 1433.515 | 328.18000000000006 | 1354.7073846153849 |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | [Target Cell] | 840.888  | 31.86650000000003  | 809.0215000000001  |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |               |          |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024       | 1149.891 | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477      | 1149.891 | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |               |          |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667       | 1103.03  | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667       | 830.358  | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |               |          |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |               |          |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |               |          |                    |                    |
| 13 | DDR_A9    | 2          | 1419.369     |     |           |               |          |                    |                    |



min_row: 1
max_row: 13
min_col: 1
max_col: 9
target_cell_row_idx: 3
target_cell_col_idx: 6
target_cell_value: 777.155
formula: =MIN(C2:C3)
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      |
|---:|----:|:--------------|:-------|
|  1 |   0 |               |        |
|  2 |   0 |               |        |
|  3 |   0 |               |        |
|  4 |   1 | 8             | 8.0    |
|  5 |   1 | [Target Cell] | 16.0   |
|  6 |   1 | 32            | 32.0   |
|  7 |   0 | 64            | 0.0    |
|  8 |   0 | 128           | 0.0    |
|  9 |   1 | 256           | 256.0  |
| 10 |   0 | 512           | 0.0    |
| 11 |   0 | 1024          | 0.0    |
| 12 |   0 | 2048          | 0.0    |
| 13 |   1 | 4096          | 4096.0 |
| 14 |   1 | 8192          | 8192.0 |
| 15 |   0 | 16384         | 0.0    |



min_row: 1
max_row: 15
min_col: 1
max_col: 3
target_cell_row_idx: 5
target_cell_col_idx: 2
target_cell_value: 16
formula: =2*B4
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             |
|---:|:----|:--------|:--------------|
|  7 | 0.0 | 64.0    | 0             |
|  8 | 0.0 | 128.0   | 0             |
|  9 | 1.0 | 256.0   | 256           |
| 10 | 0.0 | 512.0   | 0             |
| 11 | 0.0 | 1024.0  | 0             |
| 12 | 0.0 | 2048.0  | 0             |
| 13 | 1.0 | 4096.0  | 4096          |
| 14 | 1.0 | 8192.0  | 8192          |
| 15 | 0.0 | 16384.0 | 0             |
| 16 | 0.0 |         |               |
| 17 |     |         | [Target Cell] |



min_row: 7
max_row: 17
min_col: 1
max_col: 3
target_cell_row_idx: 17
target_cell_col_idx: 3
target_cell_value: 12600
formula: =SUM(C4:C16)
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 | Name      | Node Count | Routed (mil) |     |           | Min      | Max      | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | 777.155  | 1433.515 | [Target Cell]      | 1354.7073846153849 |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | 777.155  | 840.888  | 31.86650000000003  | 809.0215000000001  |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |          |          |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024  | 1149.891 | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477 | 1149.891 | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |          |          |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667  | 1103.03  | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667  | 830.358  | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |          |          |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |          |          |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |          |          |                    |                    |



min_row: 1
max_row: 12
min_col: 1
max_col: 9
target_cell_row_idx: 2
target_cell_col_idx: 8
target_cell_value: 328.18000000000006
formula: =(G2-F2)/2
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 | Name      | Node Count | Routed (mil) |     |           | Min      | Max      | Skew               | Average length     |
|  2 | DDR_CLK_N | 2          | 840.888      |     | ADDR_CTRL | 777.155  | 1433.515 | 328.18000000000006 | 1354.7073846153849 |
|  3 | DDR_CLK_P | 2          | 777.155      |     | CK        | 777.155  | 840.888  | 31.86650000000003  | [Target Cell]      |
|  4 | DDR_A0    | 2          | 1413.9       |     |           |          |          |                    |                    |
|  5 | DDR_A1    | 2          | 1401.121     |     | DQ0       | 908.024  | 1149.891 | 120.93350000000004 | 986.1542727272728  |
|  6 | DDR_A2    | 2          | 1394.369     |     | DQS0      | 1148.477 | 1149.891 | 0.7069999999999936 | 1149.1840000000002 |
|  7 | DDR_A3    | 2          | 1414.144     |     |           |          |          |                    |                    |
|  8 | DDR_A4    | 2          | 1403.327     |     | DQ1       | 829.667  | 1103.03  | 136.68149999999997 | 993.6182727272728  |
|  9 | DDR_A5    | 2          | 1395.802     |     | DQS1      | 829.667  | 830.358  | 0.3454999999999586 | 830.0125           |
| 10 | DDR_A6    | 2          | 1361.363     |     |           |          |          |                    |                    |
| 11 | DDR_A7    | 2          | 1396.377     |     |           |          |          |                    |                    |
| 12 | DDR_A8    | 2          | 1397.515     |     |           |          |          |                    |                    |
| 13 | DDR_A9    | 2          | 1419.369     |     |           |          |          |                    |                    |



min_row: 1
max_row: 13
min_col: 1
max_col: 9
target_cell_row_idx: 3
target_cell_col_idx: 9
target_cell_value: 809.0215000000001
formula: =AVERAGE(C2:C3)
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   |
|---:|:----|:--------------------|:-------------------|:----|
|  2 |     | User-Input Cells    |                    |     |
|  3 |     | Calculated Cells    |                    |     |
|  4 |     | Constants Cells     |                    |     |
|  5 |     |                     |                    |     |
|  6 |     | Ven (V)             | 1.25               |     |
|  7 |     | Ip (A)              | 1e-06              |     |
|  8 |     | Ih (A)              | 3e-06              |     |
|  9 |     | vinstart (V)        | 6.5                |     |
| 10 |     | vinstop (V)         | 6                  |     |
| 11 |     | R1 (kOhm)           | 166.66666666666666 |     |
| 12 |     | R2 (kOhm)           | [Target Cell]      |     |
| 13 |     | R1_actual (kOhm)    | 165                |     |
| 14 |     | R2_actual (kOhm)    | 38.3               |     |
| 15 |     | vinstart_actual (V) | 6.470117493472586  |     |
| 16 |     | vinstop_actual (V)  | 5.9751174934725855 |     |
| 17 |     |                     |                    |     |
| 18 |     |                     |                    |     |
| 19 |     |                     |                    |     |
| 20 |     |                     |                    |     |
| 21 |     |                     |                    |     |
| 22 |     |                     |                    |     |



min_row: 2
max_row: 22
min_col: 1
max_col: 4
target_cell_row_idx: 12
target_cell_col_idx: 3
target_cell_value: 38.46153846153847
formula: =C6/((C9-C6)/(C11*1000)+C7)/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     | D    | E   | F   | G      | H     | I             | J   | K   | L   | M   | N      | O     | P    | Q   | R   |
|---:|:----|:------|:------|:-----|:----|:----|:-------|:------|:--------------|:----|:----|:----|:----|:-------|:------|:-----|:----|:----|
| 26 | 23  | 17    | 544   | 220  |     | 23  | 17     | 544   | 220           |     | 0.0 |     | 23  | 17     | 544   | 220  |     | 0.0 |
| 27 | 24  | 18    | 1024  | 400  |     | 24  | 18     | 1024  | 400           |     | 0.0 |     | 24  | 18     | 1024  | 400  |     | 0.0 |
| 28 | 25  | 19    | 32801 | 8021 |     | 25  | 19     | 32801 | 8021          |     | 0.0 |     | 25  | 19     | 32801 | 8021 |     | 0.0 |
| 29 | 26  | 1A    | 0     | 0    |     | 26  | 1A     | 0     | 0             |     | 0.0 |     | 26  | 1A     | 0     | 0    |     | 0.0 |
| 30 | 27  | 1B    | 125   | 7D   |     | 27  | 1B     | 125   | 7D            |     | 0.0 |     | 27  | 1B     | 125   | 7D   |     | 0.0 |
| 31 | 28  | 1C    | 1518  | 5EE  |     | 28  | 1C     | 1518  | 5EE           |     | 0.0 |     | 28  | 1C     | 1518  | 5EE  |     | 0.0 |
| 32 | 29  | 1D    | 0     | 0    |     | 29  | 1D     | 0     | 0             |     | 0.0 |     | 29  | 1D     | 0     | 0    |     | 0.0 |
| 33 | 30  | 1E    | 2     | 2    |     | 30  | 1E     | 2     | 2             |     | 0.0 |     | 30  | 1E     | 2     | 2    |     | 0.0 |
| 34 | 31  | 1F    | 0     | 0    |     | 31  | 1F     | 0     | 0             |     | 0.0 |     | 31  | 1F     | 0     | 0    |     | 0.0 |
| 35 |     |       |       |      |     |     |        |       |               |     |     |     |     |        |       |      |     |     |
| 36 |     | 0x467 | 8193  | 8FCC |     |     | 0x0467 | 8193  | [Target Cell] |     | 0.0 |     |     | 0x0467 | 8193  | 2001 |     | 0.0 |
| 37 |     | 0x468 | 0     | 2001 |     |     | 0x0468 | 0     | 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: 9
target_cell_value: 2001
formula: =DEC2HEX(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   | C        | D        | E             |
|---:|:---------|:----|:---------|:---------|:--------------|
|  1 | 电压 V   |     | max      | min      | max-min       |
|  2 | 0.2      |     | 0.210375 | 0.187875 | [Target Cell] |
|  3 | 0.193687 |     |          |          |               |
|  4 | 0.199563 |     |          |          |               |
|  5 | 0.199437 |     |          |          |               |
|  6 | 0.1985   |     |          |          |               |
|  7 | 0.197938 |     |          |          |               |
|  8 | 0.198437 |     |          |          |               |
|  9 | 0.1985   |     |          |          |               |
| 10 | 0.199563 |     |          |          |               |
| 11 | 0.198313 |     |          |          |               |
| 12 | 0.198313 |     |          |          |               |



min_row: 1
max_row: 12
min_col: 1
max_col: 5
target_cell_row_idx: 2
target_cell_col_idx: 5
target_cell_value: 0.02250000000000002
formula: =C2-D2
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                   |
|---:|:---------|:----|:--------------|:---------|:--------------------|
|  1 | 电压 V   |     | max           | min      | max-min             |
|  2 | 0.2      |     | [Target Cell] | 0.187875 | 0.02250000000000002 |
|  3 | 0.193687 |     |               |          |                     |
|  4 | 0.199563 |     |               |          |                     |
|  5 | 0.199437 |     |               |          |                     |
|  6 | 0.1985   |     |               |          |                     |
|  7 | 0.197938 |     |               |          |                     |
|  8 | 0.198437 |     |               |          |                     |
|  9 | 0.1985   |     |               |          |                     |
| 10 | 0.199563 |     |               |          |                     |
| 11 | 0.198313 |     |               |          |                     |
| 12 | 0.198313 |     |               |          |                     |



min_row: 1
max_row: 12
min_col: 1
max_col: 5
target_cell_row_idx: 2
target_cell_col_idx: 3
target_cell_value: 0.210375
formula: =MAX(A2:A927)
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:
|    | F   | G      | H     | I    | J   | K   | L   | M   | N      | O     | P             | Q   | R   |
|---:|:----|:-------|:------|:-----|:----|:----|:----|:----|:-------|:------|:--------------|:----|:----|
| 26 | 23  | 17     | 544   | 220  |     | 0.0 |     | 23  | 17     | 544   | 220           |     | 0.0 |
| 27 | 24  | 18     | 1024  | 400  |     | 0.0 |     | 24  | 18     | 1024  | 400           |     | 0.0 |
| 28 | 25  | 19     | 32801 | 8021 |     | 0.0 |     | 25  | 19     | 32801 | 8021          |     | 0.0 |
| 29 | 26  | 1A     | 0     | 0    |     | 0.0 |     | 26  | 1A     | 0     | 0             |     | 0.0 |
| 30 | 27  | 1B     | 125   | 7D   |     | 0.0 |     | 27  | 1B     | 125   | 7D            |     | 0.0 |
| 31 | 28  | 1C     | 1518  | 5EE  |     | 0.0 |     | 28  | 1C     | 1518  | 5EE           |     | 0.0 |
| 32 | 29  | 1D     | 0     | 0    |     | 0.0 |     | 29  | 1D     | 0     | 0             |     | 0.0 |
| 33 | 30  | 1E     | 2     | 2    |     | 0.0 |     | 30  | 1E     | 2     | 2             |     | 0.0 |
| 34 | 31  | 1F     | 0     | 0    |     | 0.0 |     | 31  | 1F     | 0     | 0             |     | 0.0 |
| 35 |     |        |       |      |     |     |     |     |        |       |               |     |     |
| 36 |     | 0x0467 | 8193  | 2001 |     | 0.0 |     |     | 0x0467 | 8193  | [Target Cell] |     | 0.0 |
| 37 |     | 0x0468 | 0     | 0    |     | 0.0 |     |     | 0x0468 | 0     | 0             |     | 0.0 |



min_row: 26
max_row: 37
min_col: 6
max_col: 18
target_cell_row_idx: 36
target_cell_col_idx: 16
target_cell_value: 2001
formula: =DEC2HEX(O36)
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           | [Target Cell]                                                     |
|  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                                                   |



min_row: 1
max_row: 13
min_col: 1
max_col: 2
target_cell_row_idx: 3
target_cell_col_idx: 2
target_cell_value: +-range (mV)
formula: ="+-range (mV)"
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                   |
|---:|:---------|:----|:---------|:--------------|:--------------------|
|  1 | 电压 V   |     | max      | min           | max-min             |
|  2 | 0.2      |     | 0.210375 | [Target Cell] | 0.02250000000000002 |
|  3 | 0.193687 |     |          |               |                     |
|  4 | 0.199563 |     |          |               |                     |
|  5 | 0.199437 |     |          |               |                     |
|  6 | 0.1985   |     |          |               |                     |
|  7 | 0.197938 |     |          |               |                     |
|  8 | 0.198437 |     |          |               |                     |
|  9 | 0.1985   |     |          |               |                     |
| 10 | 0.199563 |     |          |               |                     |
| 11 | 0.198313 |     |          |               |                     |
| 12 | 0.198313 |     |          |               |                     |



min_row: 1
max_row: 12
min_col: 1
max_col: 5
target_cell_row_idx: 2
target_cell_col_idx: 4
target_cell_value: 0.187875
formula: =MIN(A2:A927)