{"id":"W7010580143","doi":"","title":"Informatisation, productivité et emploi : des effets différenciés entre secteurs industriels selon le niveau technologique","year":2018,"lang":"fr","type":"article","venue":"Gallica (Bibliothèque nationale de France)","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Measure (data warehouse); Order (exchange); Term (time); Quarter (Canadian coin)","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":[0.002612022,0.0003937279,0.0004444736,0.0007098595,0.0003403012,0.00245534,0.0005291291,0.001230153,0.005536123],"category_scores_gemma":[0.01380427,0.0002592838,0.0009529436,0.001315949,0.0007366668,0.001117384,0.0008395535,0.001137703,0.001038501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103426,"about_ca_system_score_gemma":0.0008537048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02340856,"about_ca_topic_score_gemma":0.01131233,"domain_scores_codex":[0.9985971,0.0007231025,0.00005946551,0.0002521788,0.0002050649,0.0001629516],"domain_scores_gemma":[0.9605429,0.0333809,0.002768582,0.0009716211,0.001177604,0.001158441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009011068,0.0008041326,0.914827,0.0003293532,0.001939236,0.0003271959,0.003666714,0.006521691,0.004673885,0.001713487,0.00102101,0.05516528],"study_design_scores_gemma":[0.00009507812,0.000632396,0.9901603,0.00005448798,0.0007175987,0.00009677804,0.001692551,0.002389546,0.001770479,0.0007203399,0.001651535,0.00001903057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968798,0.0008726519,0.0002361132,0.0002186207,0.000008764358,0.000004330912,0.0002880422,0.00001860738,0.001472985],"genre_scores_gemma":[0.9976743,0.0003036712,0.0001645411,0.00004315549,0.000008846732,0.000007710167,0.0002492125,0.00001063232,0.001538069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02340856,"threshold_uncertainty_score":0.04654461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885854721142181,"score_gpt":0.2271639723763439,"score_spread":0.2083054251649221,"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."}}