{"id":"W3015971772","doi":"10.14738/abr.82.7804","title":"Wage Inequality, Firm Size and Gender: The Case of CANADA","year":2020,"lang":"en","type":"article","venue":"Archives of Business Research","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Wage inequality; Inequality; Economics; Wage; Labour economics; Gender inequality; Demographic economics","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":[0.001091287,0.0003088403,0.0006483501,0.002964397,0.005494856,0.002770249,0.001762008,0.001011666,0.004780578],"category_scores_gemma":[0.005688461,0.0002473449,0.0007458584,0.01137035,0.001628405,0.000995994,0.001681018,0.001575949,0.0003286084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03658209,"about_ca_system_score_gemma":0.04600907,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982209,"about_ca_topic_score_gemma":0.9991751,"domain_scores_codex":[0.9979583,0.0001124882,0.00005061343,0.0001910768,0.0004427498,0.001244755],"domain_scores_gemma":[0.9946243,0.0006439632,0.001137254,0.0001937949,0.001781555,0.001618966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000219658,0.00008063216,0.9458356,0.0001126458,0.0001347065,0.0009147994,0.004788941,0.001055934,0.0001355526,0.009171257,0.01753501,0.02001517],"study_design_scores_gemma":[0.00001719994,0.00001473703,0.983371,0.0001516218,0.00006994716,0.0001403474,0.007244719,0.001083916,0.00007229482,0.0009104578,0.006888832,0.00003493103],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9536149,0.006007651,0.000231202,0.007682027,0.00006018119,0.00004420499,0.01191339,0.00002501625,0.02042139],"genre_scores_gemma":[0.9929579,0.001552868,0.0001489472,0.0003352006,0.00001684129,0.00001112923,0.001950036,0.00001067065,0.003016367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03658209,"threshold_uncertainty_score":0.2654229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2404190310581028,"score_gpt":0.4633696405606565,"score_spread":0.2229506095025537,"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."}}