{"id":"W6945288878","doi":"10.25318/1310002301-fra","title":"https://www150.statcan.gc.ca/t1/tbl1/fr/tv.action?pid=1310002301&request_locale=fr","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arterial disease; Medical screening; Limiting","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000441039,0.001058614,0.0008694573,0.0001684595,0.0006881984,0.0003194457,0.0009848129,0.0005422794,0.3386645],"category_scores_gemma":[0.0006224004,0.001224502,0.0001366094,0.000829083,0.0005317719,0.000455224,0.0003399139,0.001012809,0.0172979],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01833883,"about_ca_system_score_gemma":0.001153195,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7927173,"about_ca_topic_score_gemma":0.9692149,"domain_scores_codex":[0.9931393,0.0002947114,0.001281895,0.001395104,0.002439559,0.00144939],"domain_scores_gemma":[0.9959024,0.0007834144,0.001002801,0.001204511,0.0002791021,0.0008278245],"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":[0.00004305291,0.0002068557,0.0006346694,0.000498701,0.00008031126,0.000173396,0.00009042558,0.0001603744,0.0003528834,0.0037939,0.985686,0.008279406],"study_design_scores_gemma":[0.0004648918,0.0001535465,0.05137583,0.0002396788,0.000300924,0.0000407106,0.003465734,0.001589855,0.0003548266,0.0001738159,0.9405164,0.001323794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001776126,0.0003758702,0.003144145,0.0009246852,0.005242415,0.000964952,0.9821433,0.00004201568,0.005386505],"genre_scores_gemma":[0.01102606,0.002354814,0.0003346587,0.0006863135,0.0002984568,0.0001212036,0.9691195,0.0001023527,0.01595665],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3213666,"threshold_uncertainty_score":0.9990205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01998910791024751,"score_gpt":0.2815231082081142,"score_spread":0.2615340002978667,"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."}}