Version history

{
  "scope": "Mouse cerebral cortex (per paper title/abstract)",
  "claim_text": "The dynamic models presented in this paper provide a quantitative framework for adding putative temporal dynamics to the static description of a neuronal circuit from single time-point connectomics e…",
  "raw_fields": {
    "n": 0,
    "doi": "10.1523/jneurosci.2917-14.2015",
    "claim": "The dynamic models presented in this paper provide a quantitative framework for adding putative temporal dynamics to the static description of a neuronal circuit from single time-point connectomics e…",
    "cite_key": "Loewenstein2015",
    "evidence": "Predicting the Dynamics of Network Connectivity in the Neocortex",
    "effect_size": null,
    "text_access": "abstract_only",
    "study_system": "Mouse cerebral cortex (per paper title/abstract)",
    "argument_role": "supporting",
    "replication_status": "replication_unknown",
    "claim_source_sentence": "The dynamic models presented in this paper provide a quantitative framework for adding putative temporal dynamics to the static description of a neuronal circuit from single time-point connectomics experiments.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [],
    "claim_rewritten_from_source": true,
    "effect_size_source_sentence": null
  },
  "section_id": "section_12",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_12_evidence_package.json",
  "effect_size": null,
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-12-plasticity",
  "source_kind": "review_finding",
  "source_path": "evidence/section_12_evidence_package.json",
  "source_refs": [
    "paper:paper-32164922d2a1"
  ],
  "source_span": "The dynamic models presented in this paper provide a quantitative framework for adding putative temporal dynamics to the static description of a neuronal circuit from single time-point connectomics experiments.",
  "study_system": "Mouse cerebral cortex (per paper title/abstract)",
  "evidence_refs": [
    {
      "ref": "paper:paper-32164922d2a1"
    }
  ],
  "section_title": "12. Plasticity at E→E synapses in mouse — Hebbian, STDP, behavioural-time-scale plasticity; how plasticity shapes the recurrent matrix during learning",
  "source_policy": {
    "mode": "public_source_pointer_with_short_context",
    "notes": [
      "Local review repositories are read-only inputs.",
      "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
    ],
    "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
    "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
  },
  "evidence_summary": "Predicting the Dynamics of Network Connectivity in the Neocortex",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "replication_unknown",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-12-plasticity",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_12_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}