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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
method: string
generated_at: string
free_parameters: int64
authority_sha256: string
stance: string
n_claims: int64
claims: list<item: struct<id: string, tier: string, statement: string, evidence: struct<authority_ok: bool,  (... 938 chars omitted)
  child 0, item: struct<id: string, tier: string, statement: string, evidence: struct<authority_ok: bool, authority_s (... 926 chars omitted)
      child 0, id: string
      child 1, tier: string
      child 2, statement: string
      child 3, evidence: struct<authority_ok: bool, authority_sha256: string, float_engine_ok: bool, all_green: bool, pass: i (... 851 chars omitted)
          child 0, authority_ok: bool
          child 1, authority_sha256: string
          child 2, float_engine_ok: bool
          child 3, all_green: bool
          child 4, pass: int64
          child 5, fail: int64
          child 6, pooled_median_of_domain_medians_pct: double
          child 7, max_pooled_domain_median_pct: double
          child 8, worst_scalar_domain: string
          child 9, worst_scalar_max_error_pct: double
          child 10, verdict: string
          child 11, pooled: double
          child 12, max: double
          child 13, within: int64
          child 14, n: int64
          child 15, baseline: double
          child 16, ok: bool
          child 17, max_rel_error_pct: double
          child 18, median_rel_error_pct: double
          child 19, n_core: int64
          child 20, n_emergence_core: int64
          child 21, n_total:
...
dictions: int64
          child 24, n_domains: int64
          child 25, domains: list<item: string>
              child 0, item: string
          child 26, n_engineering_fuel_related: int64
          child 27, source: string
          child 28, free_parameters: int64
          child 29, domain: string
          child 30, branch: string
          child 31, note: string
          child 32, benchmark_domains_green: string
          child 33, pooled_median_of_domains_pct: double
          child 34, worst_domain_max_scalar_pct: double
          child 35, unique_formulas_live_ok: double
      child 4, bold: bool
core_panel: list<item: struct<domain: string, S: double, D_eff: int64, regime: string, cluster: string, T1: doub (... 28 chars omitted)
  child 0, item: struct<domain: string, S: double, D_eff: int64, regime: string, cluster: string, T1: double, T2: dou (... 16 chars omitted)
      child 0, domain: string
      child 1, S: double
      child 2, D_eff: int64
      child 3, regime: string
      child 4, cluster: string
      child 5, T1: double
      child 6, T2: double
      child 7, T3: double
thresholds: struct<green_gate_pooled_median_pct: double, contested_baseline_pct: double>
  child 0, green_gate_pooled_median_pct: double
  child 1, contested_baseline_pct: double
package: string
version: string
chat_model: string
features: list<item: string>
  child 0, item: string
code: string
kaggle: string
theory: string
authority: string
git_commit_hint: string
updated_at: string
to
{'package': Value('string'), 'version': Value('string'), 'updated_at': Value('string'), 'free_parameters': Value('int64'), 'authority': Value('string'), 'code': Value('string'), 'theory': Value('string'), 'chat_model': Value('string'), 'kaggle': Value('string'), 'features': List(Value('string')), 'git_commit_hint': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              method: string
              generated_at: string
              free_parameters: int64
              authority_sha256: string
              stance: string
              n_claims: int64
              claims: list<item: struct<id: string, tier: string, statement: string, evidence: struct<authority_ok: bool,  (... 938 chars omitted)
                child 0, item: struct<id: string, tier: string, statement: string, evidence: struct<authority_ok: bool, authority_s (... 926 chars omitted)
                    child 0, id: string
                    child 1, tier: string
                    child 2, statement: string
                    child 3, evidence: struct<authority_ok: bool, authority_sha256: string, float_engine_ok: bool, all_green: bool, pass: i (... 851 chars omitted)
                        child 0, authority_ok: bool
                        child 1, authority_sha256: string
                        child 2, float_engine_ok: bool
                        child 3, all_green: bool
                        child 4, pass: int64
                        child 5, fail: int64
                        child 6, pooled_median_of_domain_medians_pct: double
                        child 7, max_pooled_domain_median_pct: double
                        child 8, worst_scalar_domain: string
                        child 9, worst_scalar_max_error_pct: double
                        child 10, verdict: string
                        child 11, pooled: double
                        child 12, max: double
                        child 13, within: int64
                        child 14, n: int64
                        child 15, baseline: double
                        child 16, ok: bool
                        child 17, max_rel_error_pct: double
                        child 18, median_rel_error_pct: double
                        child 19, n_core: int64
                        child 20, n_emergence_core: int64
                        child 21, n_total:
              ...
              dictions: int64
                        child 24, n_domains: int64
                        child 25, domains: list<item: string>
                            child 0, item: string
                        child 26, n_engineering_fuel_related: int64
                        child 27, source: string
                        child 28, free_parameters: int64
                        child 29, domain: string
                        child 30, branch: string
                        child 31, note: string
                        child 32, benchmark_domains_green: string
                        child 33, pooled_median_of_domains_pct: double
                        child 34, worst_domain_max_scalar_pct: double
                        child 35, unique_formulas_live_ok: double
                    child 4, bold: bool
              core_panel: list<item: struct<domain: string, S: double, D_eff: int64, regime: string, cluster: string, T1: doub (... 28 chars omitted)
                child 0, item: struct<domain: string, S: double, D_eff: int64, regime: string, cluster: string, T1: double, T2: dou (... 16 chars omitted)
                    child 0, domain: string
                    child 1, S: double
                    child 2, D_eff: int64
                    child 3, regime: string
                    child 4, cluster: string
                    child 5, T1: double
                    child 6, T2: double
                    child 7, T3: double
              thresholds: struct<green_gate_pooled_median_pct: double, contested_baseline_pct: double>
                child 0, green_gate_pooled_median_pct: double
                child 1, contested_baseline_pct: double
              package: string
              version: string
              chat_model: string
              features: list<item: string>
                child 0, item: string
              code: string
              kaggle: string
              theory: string
              authority: string
              git_commit_hint: string
              updated_at: string
              to
              {'package': Value('string'), 'version': Value('string'), 'updated_at': Value('string'), 'free_parameters': Value('int64'), 'authority': Value('string'), 'code': Value('string'), 'theory': Value('string'), 'chat_model': Value('string'), 'kaggle': Value('string'), 'features': List(Value('string')), 'git_commit_hint': Value('string')}
              because column names don't match

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FSOT Universe Monte Carlo Intelligence

Simulate the universe under Fluid Spacetime Omni-Theory (FSOT) — discover pathways and physics.

This is not a market product.

Author Damian Arthur Palumbo
Authority pin D1D38A · free_parameters = 0
Theory law court FSOT-2.1-Lean
Code FSOT-Monte-Carlo-Intelligence
Chat model weights dappalumbo91/FSOT-Qwen2.5-7B-Instruct

Claim tiers (do not conflate)

Tier Meaning
MEASURED Pin, zero free params, archive green-gate ≤0.5% numbers
STRUCTURE Multipath map occupancy / flip rates (not the green gate)
PREREG PRED-* until lab pass under discriminant
Soft court promote_candidatenot Lean-proved

What it does

  1. 402-domain atlas (35 core + 367 extension panels) under one fluid law
  2. Multipath Monte Carlo with observer collapse as thought
  3. Connective tissue graph + tissue theses
  4. PRED bench-closure with kill criteria + priority lab queue
  5. Flip-hotspot experiment protocols
  6. Soft formal court → Lean candidates (batch, not per-path)
  7. Qwen mouth (docs RAG + optional adaptive LoRA on articulation only)

Quickstart

git clone https://github.com/dappalumbo91/FSOT-Monte-Carlo-Intelligence.git
cd FSOT-Monte-Carlo-Intelligence
pip install -r requirements.txt
python -m fsot_mc gate
python -m fsot_mc improve --n-paths 64
python -m fsot_mc serve --port 8765

Windows: double-click START_FSOT.bat after first install.

Visual UI (v1.5)

  • 2D / 3D toggle in the top bar (Three.js CDN for 3D)
  • As Above So Below: hue = physics spine · ring/height = D_eff · pie sectors = kinship
  • Expansion shells: center = seeds/K · outer = higher scale · bright axons = domain signals

free_parameters = 0 · Research only · MIT

Repos

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