{"id":"W7106036171","doi":"10.5281/zenodo.17644207","title":"CNeuroMod documentation version 82adf004","year":2025,"lang":"","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Documentation; Technical documentation; Data collection; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001051836,0.001171148,0.001014654,0.001835381,0.0007305183,0.002218795,0.002141039,0.001311205,0.6079019],"category_scores_gemma":[0.002392744,0.0007264979,0.0006058784,0.001750023,0.0002977276,0.002092476,0.001160692,0.0013872,0.456994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126649,"about_ca_system_score_gemma":0.001295031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008694953,"about_ca_topic_score_gemma":0.01060259,"domain_scores_codex":[0.9993338,0.00005481686,0.00004582636,0.0001346778,0.0003826543,0.0000482065],"domain_scores_gemma":[0.9979799,0.000334068,0.00009579791,0.0004812965,0.0009409148,0.0001680046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000118884,0.0000196233,0.0001147973,0.0003223066,0.000009287342,0.0000364809,0.00003460933,0.0006199672,0.003471362,0.006713648,0.9362503,0.0522887],"study_design_scores_gemma":[0.00006205508,0.00001575085,0.000427388,0.00006226362,0.00001322548,0.0001226531,0.0000157174,0.00299257,0.004188131,0.004193416,0.9878846,0.00002235377],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.001936385,0.001576626,0.153959,0.001337427,0.002456316,0.0002826406,0.3972341,0.09506623,0.3461513],"genre_scores_gemma":[0.01392679,0.001134975,0.05333827,0.0004633974,0.0003879344,0.0007109437,0.3891391,0.05963682,0.4812618],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.3920981,"threshold_uncertainty_score":0.5592803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240562040761289,"score_gpt":0.2604271909040677,"score_spread":0.2363709868279388,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}