{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001050751,0.001508525,0.001508765,0.005171488,0.0008638827,0.003813389,0.002893502,0.001621059,0.1760327],"category_scores_gemma":[0.01043837,0.001071784,0.001280006,0.01526093,0.0005258091,0.001503967,0.001679819,0.001719985,0.1790915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005020149,"about_ca_system_score_gemma":0.01015986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4730523,"about_ca_topic_score_gemma":0.5259469,"domain_scores_codex":[0.998892,0.0001358567,0.0001192116,0.000295481,0.0003145529,0.0002429179],"domain_scores_gemma":[0.9948528,0.001358288,0.0004161128,0.0008428703,0.002115648,0.0004141955],"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":[0.00002744543,0.000006066982,0.0007123387,0.0003911263,0.00002278967,0.000007775738,0.00001671423,0.000137796,0.00002820824,0.0003000998,0.9968677,0.001481873],"study_design_scores_gemma":[0.0001397726,0.000004382348,0.005192171,0.0003835599,0.00003114982,0.00001715218,0.00008203488,0.0002725872,0.0002232439,0.0007478531,0.9928761,0.00003004343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002141872,0.0000214947,0.00002830155,0.00003431992,0.000006799787,0.000003684517,0.9990044,0.0002236809,0.0006558672],"genre_scores_gemma":[0.0003665527,0.00007012898,0.0002294538,0.00005242174,0.000004932734,0.00004665404,0.9977716,0.000213526,0.001244746],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8239673,"threshold_uncertainty_score":0.9405977,"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."}}