{"id":"W7020430616","doi":"","title":"Les programmes de développements de talents des gestionnaires oeuvrant au sein des multinationales : composantes et déterminants","year":2012,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Field (mathematics); Work (physics); Legislation; Qualitative research","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002686463,0.0004921101,0.0002192664,0.001773523,0.002752751,0.002369692,0.001092185,0.0006844361,0.04691508],"category_scores_gemma":[0.0048008,0.0002771254,0.0003124293,0.002051248,0.00126542,0.001213265,0.00280591,0.001270517,0.005621723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006927939,"about_ca_system_score_gemma":0.0123967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05764225,"about_ca_topic_score_gemma":0.08648349,"domain_scores_codex":[0.9983045,0.0004747065,0.00006239155,0.0001521565,0.0004565212,0.0005497118],"domain_scores_gemma":[0.9959428,0.0009278333,0.0002881113,0.0003654561,0.001049991,0.001425752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009988789,0.0007299564,0.04637079,0.0006177991,0.00003242297,0.0004803323,0.02454911,0.002413355,0.008801777,0.08119339,0.03308041,0.8007319],"study_design_scores_gemma":[0.00009483922,0.0007833494,0.3346184,0.0003054785,0.0000241432,0.0003132144,0.01303201,0.001354912,0.005039758,0.002935019,0.6414623,0.00003654251],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5976411,0.00203655,0.006348855,0.003251179,0.000167872,0.0006220969,0.002647955,0.0006208757,0.3866636],"genre_scores_gemma":[0.3906209,0.001230431,0.00996291,0.0002091355,0.00006369944,0.0006117794,0.001595776,0.0002073436,0.5954981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05764225,"threshold_uncertainty_score":0.1569466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574619788065107,"score_gpt":0.2171528011444225,"score_spread":0.2014066032637715,"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."}}