{"id":"W6963830280","doi":"10.25318/2710012601-fra","title":"Innovation et stratégies d'entreprise, pratiques de résolution des problèmes de rendement, 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":"Productivity; Statistical analysis; Context (archaeology); Production (economics); Field (mathematics)","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":[0.00145767,0.001270241,0.000939554,0.005078466,0.001032275,0.002605172,0.002480792,0.00178303,0.02922155],"category_scores_gemma":[0.01070279,0.0005512162,0.001150095,0.01152983,0.0005258617,0.001429035,0.001318158,0.002198528,0.02136919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00789418,"about_ca_system_score_gemma":0.01325623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6216748,"about_ca_topic_score_gemma":0.7573846,"domain_scores_codex":[0.9985757,0.0001925761,0.0001776829,0.0002903465,0.0004358655,0.0003277224],"domain_scores_gemma":[0.9944667,0.001412993,0.0006133395,0.0006834168,0.002394953,0.000428584],"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":[0.00004905197,0.00002195303,0.005404487,0.0005538239,0.00002762541,0.00001519811,0.00007626398,0.0004844955,0.00004913901,0.001980751,0.987954,0.003383174],"study_design_scores_gemma":[0.0001218554,0.00001064314,0.03057634,0.0005276193,0.00003834657,0.00003136862,0.0003287222,0.0006592902,0.0002057447,0.001512982,0.9659491,0.0000379796],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003290601,0.0001143593,0.00006530073,0.0001505553,0.00002214287,0.000009956464,0.9979782,0.00004775813,0.001282709],"genre_scores_gemma":[0.00154938,0.0001815209,0.0003812166,0.00006695103,0.00001059876,0.00008223237,0.9950746,0.00002682851,0.002626663],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3783252,"threshold_uncertainty_score":0.7611064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650641890015149,"score_gpt":0.3105995506933319,"score_spread":0.2940931317931804,"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."}}