Details
- scope
- Mouse neocortex
- claim_text
- A foundation model trained on the MICrONS dataset accurately classified anatomically defined excitatory cell types from functional recordings, across >70,000 neurons.
- section_id
- section_06
- source_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_06_evidence_package.json
- effect_size
- >70,000 neurons
- review_repo
- ComputationalReviewRecurrence
- section_ref
- wiki_page:computationalreviewrecurrence-06-connectomic-micons
- source_kind
- review_finding
- source_path
- evidence/section_06_evidence_package.json
- source_span
- In the Machine Intelligence from Cortical Networks (MICrONS) dataset, which contains functional recordings and nanoscale anatomy of more than 70,000 neurons, our model accurately classified anatomically defined types of excitatory neurons.
- study_system
- Mouse neocortex
- section_title
- 6. Connectomic resolution — MICrONS mouse V1/HVA millimetre-scale EM volume; pyramidal-pyramidal wiring statistics derived from it; reconciliation with paired-recording estimates
- evidence_summary
- Trained foundation model evaluated against EM-defined excitatory cell-type labels in MICrONS.
- review_bundle_ref
- analysis_bundle:ab-d9c479db9be9
- replication_status
- replication_unknown
- review_package_ref
- analysis_bundle:ab-d9c479db9be9
- source_artifact_ref
- wiki_page:computationalreviewrecurrence-06-connectomic-micons
- origin_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_06_evidence_package.json
- commit_sha
- 79ce062d54a924ce05953ec90aa9d26044d2b48f
- created_by
- persona-jerome-lecoq-gbo-neuroscience
- repository_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence
Raw fields (4)
- raw_fields
{ "n": 70000, "doi": "10.1038/s41586-025-08829-y", "claim": "A foundation model trained on the MICrONS dataset accurately classified anatomically defined excitatory cell types from functional recordings, across >70,000 neurons.", "cite_key": "Wang2025b", "evidence": "Trained foundation model evaluated against EM-defined excitatory cell-type labels in MICrONS.", "effect_size": ">70,000 neurons", "text_access": "fulltext", "study_system": "Mouse neocortex", "argument_role": "supporting", "replication_status": "replication_unknown", "claim_source_sentence": "In the Machine Intelligence from Cortical Networks (MICrONS) dataset, which contains functional recordings and nanoscale anatomy of more than 70,000 neurons, our model accurately classified anatomically defined types of excitatory neurons.", "source_provenance_status": "ok", "replication_evidence_dois": [], "effect_size_source_sentence": "In the Machine Intelligence from Cortical Networks (MICrONS) dataset, which contains functional recordings and nanoscale anatomy of more than 70,000 neurons, our model accurately classified anatomically defined types of excitatory neurons." }- source_refs
[ "paper:paper-a802f6ac77d4" ]
- evidence_refs
[ { "ref": "paper:paper-a802f6ac77d4" } ]- 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" }