{"id":"W6888875718","doi":"10.25318/9810055701-eng","title":"Long-form data quality indicators for Indigenous peoples content: Canada, provinces and territories, census metropolitan areas, census agglomerations and census subdivisions","year":2022,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Urban agglomeration; Indigenous; American Community Survey; Data quality","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":[0.002150382,0.001543285,0.001796605,0.005845866,0.002239273,0.002551673,0.00364105,0.001104701,0.04538187],"category_scores_gemma":[0.01777062,0.001134167,0.001411535,0.02733406,0.0005205346,0.001279222,0.001844522,0.002391296,0.01914561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02734904,"about_ca_system_score_gemma":0.0802155,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9855972,"about_ca_topic_score_gemma":0.9873865,"domain_scores_codex":[0.9967498,0.0002010316,0.0003936721,0.0003664433,0.001378709,0.0009104831],"domain_scores_gemma":[0.9820081,0.0008395055,0.0008786894,0.0006430116,0.0144704,0.001160372],"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":[0.00003017447,0.00001080375,0.002393989,0.000270657,0.00002734861,0.000008863582,0.00004214391,0.000114031,0.00001402004,0.0004323363,0.995088,0.001567725],"study_design_scores_gemma":[0.0002951693,0.00001705814,0.1491608,0.001200345,0.0001035267,0.00005186613,0.0006620898,0.0005681062,0.0002956299,0.0008395158,0.8467097,0.00009611364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001555638,0.00003596184,0.00003091333,0.00006481315,0.00001477799,0.00002655225,0.9989706,0.00003277971,0.0006680731],"genre_scores_gemma":[0.001603667,0.0001346971,0.0003961509,0.00008674854,0.000008799015,0.0002450429,0.9948978,0.00004647842,0.002580674],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04538187,"threshold_uncertainty_score":0.1984321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02943273307422207,"score_gpt":0.3149135086398026,"score_spread":0.2854807755655805,"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."}}