{"id":"W7033674578","doi":"","title":"Representation of Women and Visible Minorities on Agencies, Boards, and Commissions in Ontario","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Currency Recognition and Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Representation (politics); Government (linguistics); Context (archaeology); Agency (philosophy); Ethnic group","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003638284,0.0003383421,0.0005474759,0.0004811469,0.0003609684,0.00011976,0.0003147889,0.0002884823,0.00008064925],"category_scores_gemma":[0.0003474461,0.000371171,0.00009082312,0.0006164931,0.00004343902,0.0007221902,0.0001388139,0.0008376332,0.00001563752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007187219,"about_ca_system_score_gemma":0.0001192928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007294558,"about_ca_topic_score_gemma":0.05422463,"domain_scores_codex":[0.9976127,0.0002123494,0.0005837276,0.0007773088,0.0004690812,0.000344857],"domain_scores_gemma":[0.9986649,0.0002069365,0.0003228475,0.0003781242,0.0001537197,0.0002735178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008522993,0.0005052694,0.001890422,0.001224228,0.0001966929,0.0001015286,0.00320491,0.00001938569,0.02404889,0.1473029,0.00004566058,0.8206078],"study_design_scores_gemma":[0.009380853,0.005371841,0.2326036,0.004391629,0.0002562085,0.0001690999,0.0133565,0.002359997,0.2553515,0.321287,0.1501536,0.00531815],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960488,0.0001651454,0.000002234962,0.00002411928,0.00064515,0.000375572,0.00007957738,0.00009727522,0.03812294],"genre_scores_gemma":[0.995354,0.0002591976,0.0008788227,0.0001178256,0.00001206048,0.000089038,0.0001646109,0.00002773211,0.0030967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8152897,"threshold_uncertainty_score":0.999874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03360813566047649,"score_gpt":0.2570178011076761,"score_spread":0.2234096654471996,"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."}}