{"id":"W2149657862","doi":"10.1007/s001810200140","title":"Employer-supported training in Canada and its impact on mobility and wages","year":2003,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Receipt; Wage; Training (meteorology); Demographic economics; Psychology; Hazard; Wage growth; Affect (linguistics); Economics; Labour economics; Accounting; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008626767,0.0002083789,0.0005337847,0.0001027908,0.00005756122,0.00005795035,0.00009559084,0.00009668268,0.0001777875],"category_scores_gemma":[0.000293425,0.0002186369,0.00005267536,0.0001166445,0.00003461886,0.0001439329,0.00003735229,0.0002160407,0.00000858513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006252159,"about_ca_system_score_gemma":0.000374212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1525569,"about_ca_topic_score_gemma":0.42837,"domain_scores_codex":[0.9983744,0.00004334545,0.0006572764,0.0005293345,0.00001945986,0.0003762028],"domain_scores_gemma":[0.9991251,0.0002372293,0.0001808516,0.0002324846,0.00001293939,0.0002114235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002993657,0.00005007199,0.896815,0.00001771324,0.00003279569,0.000009126328,0.0003510103,0.0004486659,0.00000102544,0.1011622,0.00004829741,0.001034186],"study_design_scores_gemma":[0.0008131042,0.00008105304,0.8658533,0.000007938475,0.000003470923,0.000008899726,0.0001602171,0.009926055,0.00001629854,0.1184048,0.004289967,0.0004349448],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939332,0.0003175245,0.00001541202,0.0005313387,0.0001696652,0.0001674449,0.0003354863,0.00001070137,0.004519206],"genre_scores_gemma":[0.9987485,0.0003008455,0.00006327721,0.0007529622,0.00002105202,0.00001118489,0.000009633119,0.0000213728,0.00007115737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2758131,"threshold_uncertainty_score":0.8915753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04917882070245145,"score_gpt":0.2738905311876864,"score_spread":0.2247117104852349,"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."}}