{"id":"W6963834763","doi":"10.25318/2710012701-fra","title":"Innovation et stratégies d'entreprise, facteurs de promotion des employés, par industrie et la taille de l'entreprise","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Promotion (chess); Productivity; Investment (military); Context (archaeology)","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":[0.001249681,0.001244644,0.0009070276,0.005550338,0.0008353426,0.001944573,0.002146526,0.001292938,0.01408711],"category_scores_gemma":[0.008640853,0.0004069217,0.001195961,0.01108534,0.0004350392,0.001023376,0.001038205,0.001686546,0.01292511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005189053,"about_ca_system_score_gemma":0.009546166,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5330848,"about_ca_topic_score_gemma":0.6739852,"domain_scores_codex":[0.9987263,0.0001372595,0.0001650555,0.0002849369,0.0003998193,0.0002866739],"domain_scores_gemma":[0.9957144,0.001134695,0.0005773965,0.0004792843,0.001750775,0.0003434682],"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":[0.0001396994,0.00004630021,0.03337684,0.001000969,0.00008128056,0.00003782284,0.0001594868,0.0007432636,0.0001232257,0.001804261,0.9544177,0.008069145],"study_design_scores_gemma":[0.0001602781,0.00002345492,0.1418121,0.0006544521,0.00009535548,0.000082401,0.0005003945,0.001064812,0.0003776335,0.001190197,0.853983,0.00005582277],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001050092,0.0001637021,0.00005330152,0.000106898,0.00001842135,0.000009337429,0.9976296,0.00004681118,0.0009218617],"genre_scores_gemma":[0.00294464,0.0001972045,0.0002564878,0.00004240766,0.0000112098,0.00006105888,0.9945253,0.00001640668,0.001945438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4669152,"threshold_uncertainty_score":0.93933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388145469033462,"score_gpt":0.2664694115878941,"score_spread":0.2525879568975594,"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."}}