{"id":"W7072252175","doi":"","title":"(In)Visible Minorities in Canadian Health Data and Research","year":2015,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health equity; Health care; Public health; Neglect; Health data; Social determinants of health","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04599039,0.0007558347,0.001463089,0.02593934,0.007918578,0.01269884,0.002731146,0.001341368,0.009514205],"category_scores_gemma":[0.1092279,0.0007556962,0.001433209,0.05750025,0.003484148,0.002824753,0.00623174,0.001572438,0.0009048493],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07937388,"about_ca_system_score_gemma":0.2936184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9839491,"about_ca_topic_score_gemma":0.9888055,"domain_scores_codex":[0.9604924,0.009380349,0.005444977,0.002823602,0.01846736,0.003391223],"domain_scores_gemma":[0.8861519,0.03759526,0.00813336,0.008311893,0.05631147,0.003496113],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003049425,0.00004516176,0.06145306,0.03425078,0.0007942393,0.0003030411,0.02366984,0.001420325,0.0006207862,0.1904005,0.3719489,0.3147885],"study_design_scores_gemma":[0.00005477361,0.00003536983,0.05323026,0.02504181,0.000718057,0.00009122655,0.01443966,0.0006250584,0.0006166364,0.01135996,0.8936557,0.0001314739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04380816,0.2391482,0.02852561,0.1316106,0.00882523,0.002602998,0.3223217,0.00071479,0.2224427],"genre_scores_gemma":[0.5942579,0.1643332,0.08125596,0.04214916,0.002360586,0.004435093,0.08426727,0.0006100143,0.02633081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9540096,"threshold_uncertainty_score":0.5759006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2970229435281995,"score_gpt":0.3971895285798386,"score_spread":0.1001665850516392,"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."}}