Datasets:

CroviaResearch
/

crovia-continuity-monitoring-samples

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
schema: string
version: string
fields: struct<probe_id: string, probe_category: string, probe_text: string, expected_behavior: string, cade (... 106 chars omitted)
  child 0, probe_id: string
  child 1, probe_category: string
  child 2, probe_text: string
  child 3, expected_behavior: string
  child 4, cadence: string
  child 5, first_observed_at: string
  child 6, last_observed_at: string
  child 7, tpa_count: string
  child 8, drift_events: string
privacy_note: string
model_id: string
baseline_observed_at: timestamp[s]
current_response_hash: string
drift_score: double
tpa_current: string
drift_detected: bool
tpa_baseline: string
probe_category: string
current_observed_at: timestamp[s]
drift_id: string
drift_type: string
record_type: string
baseline_response_hash: string
_note: string
to
{'record_type': Value('string'), 'drift_id': Value('string'), 'model_id': Value('string'), 'probe_category': Value('string'), 'baseline_observed_at': Value('timestamp[s]'), 'current_observed_at': Value('timestamp[s]'), 'baseline_response_hash': Value('string'), 'current_response_hash': Value('string'), 'drift_detected': Value('bool'), 'drift_score': Value('float64'), 'drift_type': Value('string'), 'tpa_baseline': Value('string'), 'tpa_current': Value('string'), '_note': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              schema: string
              version: string
              fields: struct<probe_id: string, probe_category: string, probe_text: string, expected_behavior: string, cade (... 106 chars omitted)
                child 0, probe_id: string
                child 1, probe_category: string
                child 2, probe_text: string
                child 3, expected_behavior: string
                child 4, cadence: string
                child 5, first_observed_at: string
                child 6, last_observed_at: string
                child 7, tpa_count: string
                child 8, drift_events: string
              privacy_note: string
              model_id: string
              baseline_observed_at: timestamp[s]
              current_response_hash: string
              drift_score: double
              tpa_current: string
              drift_detected: bool
              tpa_baseline: string
              probe_category: string
              current_observed_at: timestamp[s]
              drift_id: string
              drift_type: string
              record_type: string
              baseline_response_hash: string
              _note: string
              to
              {'record_type': Value('string'), 'drift_id': Value('string'), 'model_id': Value('string'), 'probe_category': Value('string'), 'baseline_observed_at': Value('timestamp[s]'), 'current_observed_at': Value('timestamp[s]'), 'baseline_response_hash': Value('string'), 'current_response_hash': Value('string'), 'drift_detected': Value('bool'), 'drift_score': Value('float64'), 'drift_type': Value('string'), 'tpa_baseline': Value('string'), 'tpa_current': Value('string'), '_note': Value('string')}
              because column names don't match

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Crovia Continuity Monitoring Samples

This dataset contains synthetic samples from Crovia's continuity monitoring pipeline, which tracks behavioral consistency of AI models over time.

Purpose

AI models are updated, fine-tuned, and replaced without public disclosure of behavioral changes. Continuity monitoring provides:

Structured baselines of model behavior at specific points in time
Detection of behavioral drift between versions
Reproducible probe sets for independent verification

Methodology

Probe execution: standardized prompts are sent to AI models at regular intervals
Response hashing: responses are hashed (SHA-256, NFC-normalized) and stored with timestamps
Drift scoring: cosine similarity and hash comparison against baseline responses
Attestation: each probe result is wrapped in a TPA envelope and signed

Sample record format

{
  "probe_id": "PROBE-<example-id>",
  "model_id": "<vendor>/<model>",
  "probe_text": "[synthetic probe text]",
  "response_hash": "sha256:<example-hash>",
  "response_length": 0,
  "observed_at": "2026-01-01T00:00:00Z",
  "drift_score": null,
  "baseline_probe_id": null,
  "tpa_id": "sl_<example-receipt-id>"
}

Coverage

The production pipeline covers major publicly accessible AI systems including ChatGPT, Claude, Gemini, Grok, Mistral, and others. Samples in this dataset are synthetic and do not include real probe responses or operational data.

Verification

Production TPA records are verifiable at https://seal.croviatrust.com/v1/seal/<tpa_id>. The full ledger Merkle root is anchored to Bitcoin via OpenTimestamps.

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