{"id":"W2776953363","doi":"10.1136/bmjopen-2017-018936","title":"Our Health Counts Toronto: using respondent-driven sampling to unmask census undercounts of an urban indigenous population in Toronto, Canada","year":2017,"lang":"en","type":"article","venue":"BMJ Open","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Public Health Ontario; University of Toronto; York University","funders":"Canadian Institutes of Health Research","keywords":"Census; Respondent; Indigenous; Population; American Community Survey; Geography; Medicine; Demography; Household income; Socioeconomics; Environmental health; Political science; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007211906,0.0001386837,0.0004202341,0.00003283561,0.000209318,0.00007388049,0.0004590714,0.00007654684,0.0000678033],"category_scores_gemma":[0.0002112514,0.0001420559,0.00001879585,0.00004378488,0.000009104341,0.000401198,0.0001885846,0.00009077525,0.000005657146],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004542344,"about_ca_system_score_gemma":0.001923938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9869896,"about_ca_topic_score_gemma":0.9948727,"domain_scores_codex":[0.9983708,0.00009643943,0.000432562,0.0002832768,0.0004727963,0.000344134],"domain_scores_gemma":[0.998486,0.00001838946,0.0003221986,0.0008265193,0.00009149151,0.0002554097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002986244,0.0006084075,0.8671895,0.0006999492,0.0001776589,0.0002751273,0.04502618,0.001329607,0.00226353,0.0004027088,0.009493863,0.06954725],"study_design_scores_gemma":[0.001685903,0.0003507274,0.9680859,0.0007146561,0.00002723958,0.00002561567,0.02496846,0.0008217642,0.00005453787,0.00002965595,0.002936791,0.000298785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990407,0.000103481,0.00002392647,0.0003401047,0.0004653523,0.003663069,0.0001390625,0.00001209311,0.004845897],"genre_scores_gemma":[0.9957232,0.000007911744,0.002783403,0.0003928489,0.0001752336,0.00002847906,0.00009925284,0.00003505941,0.0007546231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1008964,"threshold_uncertainty_score":0.999279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2389009665697182,"score_gpt":0.5221689147635252,"score_spread":0.283267948193807,"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."}}