{"id":"W2955524026","doi":"","title":"Has mismatch got us down? Skills and productivity in Canada","year":2019,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Productivity; Labour economics; Human capital; Index (typography); Economics; Idle; Capital (architecture); Demographic economics; Economic growth; Computer science; Geography","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":[0.001639088,0.0002729909,0.0006038665,0.002668104,0.00300082,0.002444545,0.001159943,0.0004944809,0.003942054],"category_scores_gemma":[0.008676179,0.0002550414,0.0004827542,0.009671052,0.0009036862,0.0009219825,0.001334489,0.0008103615,0.0003535009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05111538,"about_ca_system_score_gemma":0.0598595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9985195,"about_ca_topic_score_gemma":0.9988111,"domain_scores_codex":[0.9981107,0.00009886049,0.00009184954,0.0002388736,0.0007628325,0.0006969768],"domain_scores_gemma":[0.9938094,0.000588879,0.0009116614,0.0002520896,0.003438111,0.0009998406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001566047,0.00003416394,0.95745,0.00009480801,0.0001642605,0.0001427579,0.002065592,0.001584836,0.0001883053,0.003866457,0.01038893,0.02386328],"study_design_scores_gemma":[0.00001102569,0.00001613174,0.9858583,0.00007129933,0.00003753317,0.00002902099,0.002505093,0.001653409,0.0001651899,0.0004523285,0.009169541,0.00003114465],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9573662,0.002704675,0.0004967654,0.00489862,0.00005021415,0.00002821881,0.02205204,0.00004910055,0.01235414],"genre_scores_gemma":[0.9927724,0.000802446,0.0002497376,0.0002031899,0.0000094592,0.000007532813,0.003432639,0.00001028051,0.002512232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05111538,"threshold_uncertainty_score":0.3708698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03619489552489557,"score_gpt":0.3588499312474422,"score_spread":0.3226550357225466,"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."}}