{"id":"W6926656391","doi":"10.25318/2710030301-fra","title":"Facteur de motivation principal pour l'utilisation ou le développement des bioproduits, selon l'industrie et la taille de l'entreprise","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Bacterial Infections and Vaccines","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Principal (computer security); Context (archaeology); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001435775,0.001687072,0.001389691,0.005016833,0.0009854814,0.002048341,0.002322367,0.001711445,0.01794348],"category_scores_gemma":[0.01233462,0.0005332899,0.001426164,0.01043888,0.0004887499,0.0009274358,0.001133286,0.001931764,0.01485466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006777111,"about_ca_system_score_gemma":0.01345866,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5937755,"about_ca_topic_score_gemma":0.6982042,"domain_scores_codex":[0.9982737,0.0001637831,0.0002468264,0.0003889503,0.0005759929,0.0003507408],"domain_scores_gemma":[0.9930848,0.001886758,0.0008916562,0.0005718356,0.002952235,0.0006127136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001422824,0.00003262274,0.01297399,0.0008928247,0.00009411263,0.00002546197,0.00003902957,0.0004499063,0.00005895442,0.0005732141,0.9813757,0.003341861],"study_design_scores_gemma":[0.0004299893,0.00003400641,0.1050561,0.0009625341,0.0001599755,0.0001039289,0.0002816665,0.0009218084,0.0003655678,0.0008985745,0.8907145,0.00007126285],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003737009,0.0001349508,0.00001847038,0.00007655416,0.00001502893,0.000004366875,0.9989079,0.00003744179,0.0004315609],"genre_scores_gemma":[0.001698381,0.0001767784,0.0001285045,0.00006130366,0.00001222331,0.00003876275,0.9967911,0.00001690927,0.001076084],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4062245,"threshold_uncertainty_score":0.8172338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02277936262617249,"score_gpt":0.2834065379597235,"score_spread":0.2606271753335511,"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."}}