{"id":"W3006571864","doi":"10.1504/ijhrdm.2020.10026845","title":"Training and the competitiveness of the Québec multimedia-IT sector","year":2020,"lang":"en","type":"article","venue":"International Journal of Human Resources Development and Management","topic":"Business Strategy and Innovation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"","keywords":"Training (meteorology); Diversity (politics); SWOT analysis; Business; Quality (philosophy); Order (exchange); Marketing; Knowledge management; Public relations; Political science; Finance; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001225821,0.0001571846,0.0001209734,0.001023767,0.005229152,0.003652315,0.0006498329,0.0005797001,0.01187823],"category_scores_gemma":[0.002710715,0.00009438572,0.0001208808,0.001345301,0.001828381,0.0008925875,0.001227459,0.0006702036,0.0002908988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03601251,"about_ca_system_score_gemma":0.02711076,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9375118,"about_ca_topic_score_gemma":0.9647685,"domain_scores_codex":[0.9985765,0.000334415,0.0000202003,0.0000778685,0.0003370664,0.0006538838],"domain_scores_gemma":[0.9970984,0.0005978323,0.0003706947,0.00004522367,0.0007269991,0.001160792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000491479,0.0005812328,0.4837438,0.0005233114,0.00006979161,0.004163058,0.05572858,0.005962919,0.009441984,0.096026,0.03990278,0.3033651],"study_design_scores_gemma":[0.00002413174,0.0001749502,0.6952552,0.0005368998,0.00002108613,0.0003963698,0.1141779,0.003008835,0.0012399,0.001492867,0.1835994,0.00007256059],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8981583,0.0008959359,0.0006750707,0.006423612,0.00004291005,0.00004549518,0.0002626615,0.00003389069,0.09346219],"genre_scores_gemma":[0.9934727,0.0002097045,0.0001960495,0.0002645059,0.000005707135,0.000006996471,0.00005335149,0.000004278314,0.005786751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0624882,"threshold_uncertainty_score":0.2612903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04117244971131565,"score_gpt":0.2378370489552582,"score_spread":0.1966645992439425,"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."}}