{"id":"W6963933459","doi":"10.25318/2310018901-fra","title":"Enquête sur les véhicules au Canada, nombre de véhicules dans le champ de l'enquête, 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.003390884,0.002637372,0.002318428,0.0006939548,0.002884209,0.0006441528,0.002376354,0.001760036,0.0003012368],"category_scores_gemma":[0.008200962,0.003230199,0.0002809274,0.001795967,0.0007736625,0.000746852,0.0005624741,0.002610048,0.0001459351],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.02461809,"about_ca_system_score_gemma":0.1492343,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9984519,"about_ca_topic_score_gemma":0.9998096,"domain_scores_codex":[0.9853821,0.002779153,0.002436165,0.0024109,0.0031013,0.003890341],"domain_scores_gemma":[0.9863846,0.004034384,0.002521601,0.002105658,0.002996943,0.001956819],"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":[0.0003098315,0.0008706004,0.007629615,0.002134632,0.000746951,0.001867173,0.001114486,0.0117615,0.004007298,0.0149527,0.9538335,0.0007717063],"study_design_scores_gemma":[0.002462266,0.0003408616,0.1381574,0.001846208,0.001016356,0.0007311566,0.006603726,0.02647023,0.005905726,0.0002662672,0.8120262,0.004173629],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0547906,0.001287768,0.0101595,0.002911,0.002049143,0.002269221,0.9256052,0.0001565035,0.0007710147],"genre_scores_gemma":[0.2532569,0.0009605781,0.003104603,0.00041581,0.000754331,0.000337021,0.7369512,0.0006744122,0.003545165],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1984663,"threshold_uncertainty_score":0.9996909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050387394232782,"score_gpt":0.2350069556579373,"score_spread":0.2245030817156095,"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."}}