{"id":"W1513152159","doi":"","title":"Human Capital and Productivity in British Columbia","year":2011,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human capital; Productivity; Rest (music); Immigration; Human resources; Production (economics); Demographic economics; Geography; Economic growth; Economics; Management; Medicine","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":[0.0005512557,0.0002687756,0.000354424,0.003755942,0.002969516,0.003022587,0.0007724183,0.0003994718,0.007841871],"category_scores_gemma":[0.003426737,0.000162114,0.0001809196,0.00987585,0.0008219453,0.0004775135,0.0009688372,0.0007247768,0.0008819532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05091909,"about_ca_system_score_gemma":0.04332787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9966283,"about_ca_topic_score_gemma":0.9980373,"domain_scores_codex":[0.9992367,0.0000642187,0.00003194114,0.00007497452,0.0002527809,0.0003394625],"domain_scores_gemma":[0.9967824,0.0003156552,0.000202471,0.00008826362,0.001930722,0.0006804894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001939399,0.0001836989,0.7243601,0.0003636929,0.0001817796,0.001349666,0.007361215,0.007343457,0.0007937225,0.01828307,0.09991489,0.1396707],"study_design_scores_gemma":[0.00001653016,0.00001931602,0.9449487,0.0002648281,0.0000301097,0.0001085247,0.005816273,0.001796013,0.0002235869,0.001365803,0.04535977,0.00005059531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8561113,0.006659813,0.0004590286,0.007054267,0.0001134653,0.00007390514,0.01997758,0.0001377867,0.1094129],"genre_scores_gemma":[0.9585468,0.002583036,0.0003228281,0.0002954948,0.000013022,0.00003143161,0.003551524,0.00002339096,0.03463253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05091909,"threshold_uncertainty_score":0.3694456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03709869998195919,"score_gpt":0.3177570342491036,"score_spread":0.2806583342671444,"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."}}