{"id":"W6964531782","doi":"10.25318/2310010001-fra","title":"Enquête sur les véhicules au Canada, véhicules-kilomètres, selon le type de véhicule et l'âge du modèle du véhicule, trimestriel","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Limiting; Economic shortage; Agrégation","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":[0.0006696836,0.00158701,0.001305983,0.007208242,0.00143396,0.0022812,0.001820729,0.0009693506,0.02648898],"category_scores_gemma":[0.006817095,0.0006261932,0.001312823,0.01921001,0.0005405043,0.001188475,0.001081428,0.001406795,0.01845088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01035521,"about_ca_system_score_gemma":0.02146895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9491369,"about_ca_topic_score_gemma":0.9664618,"domain_scores_codex":[0.9987487,0.00008664699,0.0001344878,0.0002954922,0.0005011308,0.0002335476],"domain_scores_gemma":[0.9953663,0.0005650432,0.0002458875,0.0003547204,0.003247185,0.0002208836],"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":[0.00009681594,0.00002172913,0.01022747,0.0008651441,0.00008573753,0.00004130581,0.0001028344,0.001026505,0.0001447842,0.0009009916,0.9780336,0.008453009],"study_design_scores_gemma":[0.00009051014,0.00001822133,0.06008708,0.0006701729,0.00008911524,0.00007790655,0.0007067327,0.001509051,0.0005648949,0.0007552456,0.935355,0.00007605874],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000771659,0.0001970967,0.0001145011,0.00008184245,0.00002327607,0.00001076648,0.9970391,0.0001664992,0.001595349],"genre_scores_gemma":[0.002423706,0.0003566562,0.0004064962,0.00004399128,0.000008389815,0.00003938016,0.9937385,0.00005163221,0.002931315],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05086309,"threshold_uncertainty_score":0.1023252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01263094242786469,"score_gpt":0.241613771764225,"score_spread":0.2289828293363604,"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."}}