{"id":"W6926512976","doi":"10.25318/3610041301-fra","title":"Historique entrées et sorties, selon les industries et le produit de base, agrégation au niveau M et le Système de classification des industries de l'Amérique du Nord (SCIAN)","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic shortage; Context (archaeology); Sugar industry; Construction industry","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":[0.0008338649,0.001579208,0.001112083,0.007585658,0.0009482544,0.001954125,0.001531033,0.0009029042,0.02405959],"category_scores_gemma":[0.00592655,0.0005810654,0.0009434048,0.01657904,0.0005051505,0.001048005,0.001041951,0.001479689,0.02337532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004403872,"about_ca_system_score_gemma":0.008299134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4236199,"about_ca_topic_score_gemma":0.5257649,"domain_scores_codex":[0.9988733,0.00009609395,0.0001470152,0.0003483917,0.0003312623,0.0002039276],"domain_scores_gemma":[0.9969161,0.0007201676,0.0003963361,0.0004040034,0.001337689,0.0002257159],"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":[0.0001148951,0.00002992753,0.01552086,0.001315966,0.00009025652,0.00005411784,0.0001411282,0.0007588812,0.0002744211,0.0009268039,0.9726918,0.00808088],"study_design_scores_gemma":[0.00008871816,0.00001116063,0.05247501,0.000426031,0.00004599149,0.00007675018,0.0002951831,0.0003382494,0.0004242104,0.0004622704,0.9453237,0.00003276148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004652713,0.000100675,0.00003965087,0.00002720091,0.000009752504,0.000004037795,0.9986519,0.00007186813,0.0006296601],"genre_scores_gemma":[0.001141319,0.0001181713,0.0002165834,0.00001560143,0.000003848367,0.00002526524,0.9975021,0.00002390982,0.0009531783],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5763801,"threshold_uncertainty_score":0.8423083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736486528558447,"score_gpt":0.2426695449340364,"score_spread":0.225304679648452,"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."}}