{"id":"W4394514297","doi":"10.6084/m9.figshare.16641028","title":"Correlation Analysis Code","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Code (set theory); Computer science; Programming language","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":[],"category_scores_codex":[0.004001562,0.002930168,0.001793397,0.005837137,0.001144852,0.00286248,0.002254644,0.002148514,0.3114134],"category_scores_gemma":[0.03864115,0.001262739,0.002902437,0.0050714,0.0006470475,0.001868492,0.002247517,0.002455221,0.2395404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001641327,"about_ca_system_score_gemma":0.004494591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01527199,"about_ca_topic_score_gemma":0.02889356,"domain_scores_codex":[0.9963282,0.0006375042,0.0006822576,0.001121842,0.0008114582,0.0004187866],"domain_scores_gemma":[0.9741847,0.01396701,0.001148828,0.004313068,0.005458409,0.0009279799],"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":[0.00008118189,0.00003341324,0.001102719,0.0004006162,0.00002780599,0.00001178517,0.00001660638,0.0001939572,0.00008696673,0.0002487041,0.994215,0.0035814],"study_design_scores_gemma":[0.001195798,0.00008812931,0.01009666,0.0006846648,0.000107145,0.0001243429,0.0001136445,0.002109246,0.0008788252,0.004757043,0.9797346,0.000109883],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001480233,0.00002911668,0.000488306,0.00007865064,0.00005139852,0.00007689064,0.9963323,0.00200965,0.0007856702],"genre_scores_gemma":[0.0006773202,0.00004187605,0.002318868,0.0001346711,0.00002044306,0.0007651817,0.9935841,0.0009093108,0.001548147],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3114134,"threshold_uncertainty_score":0.9821852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06158288836715385,"score_gpt":0.3887860496449047,"score_spread":0.3272031612777508,"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."}}