{"id":"W6945173929","doi":"10.25318/2710029901-fra","title":"Facteur de motivation principal pour l'utilisation ou le développement des biotechnologies, selon l'industrie et la taille de l'entreprise","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","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":[0.001488222,0.001633774,0.001372086,0.005663597,0.001072691,0.002211439,0.002265773,0.001604795,0.02158229],"category_scores_gemma":[0.01216257,0.0006297139,0.001244544,0.01310927,0.0005546345,0.001256599,0.001336425,0.002027646,0.01875773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008481003,"about_ca_system_score_gemma":0.01556148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7152886,"about_ca_topic_score_gemma":0.7977275,"domain_scores_codex":[0.9982272,0.0001713347,0.0002423787,0.0003412614,0.0006252177,0.0003925833],"domain_scores_gemma":[0.9922678,0.001545665,0.0008617539,0.0005727211,0.004106055,0.0006461037],"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":[0.00007756383,0.0000193458,0.006353411,0.0005554493,0.00004427566,0.00001403674,0.00003773928,0.0002704895,0.00004019732,0.0005960531,0.9897585,0.002232945],"study_design_scores_gemma":[0.0003056636,0.000019388,0.08092215,0.0006910998,0.00008738429,0.00005926265,0.0003537205,0.0006410602,0.0003020313,0.0008013336,0.915743,0.00007402422],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002644621,0.0000897528,0.0000185292,0.0000855827,0.00001609233,0.000005203515,0.9990084,0.00003390255,0.0004780864],"genre_scores_gemma":[0.00132056,0.0001555671,0.0001387148,0.0000583748,0.00001222486,0.00005453524,0.9967024,0.0000195929,0.001538013],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2847114,"threshold_uncertainty_score":0.5727761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03038333283208287,"score_gpt":0.2954795948265415,"score_spread":0.2650962619944586,"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."}}