{"id":"W7008615601","doi":"","title":"Canadian Gender Wage Gap","year":2023,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wage; Quantile regression; Quantile; Selection bias; Matching (statistics); Robustness (evolution); Selection (genetic algorithm); Workforce","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":[0.002187687,0.0005810222,0.0006322541,0.007558865,0.006850902,0.003504854,0.001716479,0.0009698743,0.05098834],"category_scores_gemma":[0.007037706,0.0002557559,0.0008476219,0.01366185,0.001069206,0.001198031,0.002199539,0.001294251,0.004185128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07442595,"about_ca_system_score_gemma":0.1035442,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9853496,"about_ca_topic_score_gemma":0.9904574,"domain_scores_codex":[0.9959491,0.0001618275,0.000110375,0.0004241416,0.002482745,0.0008717981],"domain_scores_gemma":[0.9962869,0.0002686118,0.0001686659,0.0001323844,0.002596466,0.0005470268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001298868,0.00004227034,0.03546524,0.001035438,0.00004943261,0.0004012706,0.008999067,0.0006721177,0.0003391774,0.1678541,0.4652365,0.3197756],"study_design_scores_gemma":[0.000008978986,0.00002204072,0.1172064,0.0006094028,0.00002594835,0.0002028405,0.005356753,0.000398409,0.0001760345,0.003202926,0.8727257,0.0000645361],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07776535,0.04956782,0.00252561,0.03048902,0.002952929,0.0002929649,0.1051133,0.0004227091,0.7308704],"genre_scores_gemma":[0.5630425,0.06181117,0.006547912,0.006600423,0.0005853724,0.0004047809,0.03973179,0.0003272553,0.3209487],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07442595,"threshold_uncertainty_score":0.5400006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177014714875467,"score_gpt":0.1583123319063233,"score_spread":0.1406108604187766,"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."}}