{"id":"W6950693067","doi":"10.5683/sp3/m6favr","title":"Données de recherche du Canada","year":2018,"lang":"fr","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Presentation (obstetrics); Data collection; Government (linguistics); Research data; Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006001653,0.003062938,0.002654579,0.02071479,0.005643011,0.009400428,0.003406394,0.001920812,0.1010022],"category_scores_gemma":[0.04413522,0.001143263,0.002260919,0.04447998,0.001661005,0.002387545,0.004404238,0.003512329,0.08213755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03375132,"about_ca_system_score_gemma":0.09447696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9329576,"about_ca_topic_score_gemma":0.95134,"domain_scores_codex":[0.987523,0.0009341082,0.0008808757,0.001798981,0.007590416,0.001272507],"domain_scores_gemma":[0.9631563,0.005056289,0.0008520133,0.003826552,0.02473005,0.002378826],"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":[0.00003603196,0.000006364551,0.0003954956,0.0002503791,0.00002006472,0.00002300843,0.00005683054,0.0001683233,0.00006965121,0.0007036735,0.9923255,0.005944704],"study_design_scores_gemma":[0.00003632007,0.000004124906,0.003186151,0.000320812,0.00002971808,0.00003231942,0.0001532516,0.0001900732,0.0003007322,0.0006349126,0.9950805,0.00003106345],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004061392,0.00114971,0.0003618976,0.0009801699,0.0002671473,0.00004994899,0.9841889,0.0007721657,0.01182385],"genre_scores_gemma":[0.002184956,0.001586937,0.001485604,0.0003163719,0.00007257779,0.0002396855,0.9779897,0.0005538347,0.01557021],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1010022,"threshold_uncertainty_score":0.3378861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1393762320871292,"score_gpt":0.3275982124678558,"score_spread":0.1882219803807266,"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."}}