{"id":"W7100173729","doi":"","title":"Toronto","year":2005,"lang":"en","type":"article","venue":"","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Workforce; Equity (law); Legislation; Census; Government (linguistics); Population; Diversity (politics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003942987,0.0005398649,0.0003783146,0.001078041,0.004042802,0.003977478,0.0008080952,0.00095025,0.4805631],"category_scores_gemma":[0.001961649,0.0003291517,0.0003294962,0.001554819,0.0005399225,0.001176732,0.001532665,0.0009925881,0.1414045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00519521,"about_ca_system_score_gemma":0.007127271,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3173846,"about_ca_topic_score_gemma":0.5416089,"domain_scores_codex":[0.9992835,0.00004857617,0.00002740165,0.0001841578,0.0003045212,0.0001518676],"domain_scores_gemma":[0.9986987,0.0001410418,0.00008050316,0.0001064694,0.0006806432,0.0002926919],"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":[0.0002541672,0.0001465948,0.02015262,0.0005124777,0.00002747011,0.001406676,0.003268066,0.0004296015,0.001267316,0.05145125,0.6055959,0.3154877],"study_design_scores_gemma":[0.000009863478,0.00002068575,0.008955121,0.0001374956,0.000009189126,0.0002266531,0.001488168,0.0001414224,0.0002102605,0.001259001,0.9875307,0.00001143509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01192915,0.003029614,0.000833276,0.003978305,0.0007936758,0.0001029855,0.008911147,0.0003517835,0.9700702],"genre_scores_gemma":[0.04514652,0.002939743,0.001270178,0.001437151,0.00008319486,0.00006410934,0.00433758,0.0001806144,0.944541],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6826154,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1280158563216239,"score_gpt":0.3308439241771097,"score_spread":0.2028280678554858,"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."}}