{"id":"W4235695555","doi":"10.4095/301549","title":"Visible Minority Population, 2006 - Chinese Population by Census Subdivision","year":2010,"lang":"en","type":"report","venue":"","topic":"China's Ethnic Minorities and Relations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Subdivision; Geography; Population; Demography; Sociology; Archaeology","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":[0.000340635,0.0008004908,0.0002779965,0.00247403,0.0006757884,0.0006211346,0.0007109586,0.0002500244,0.008083289],"category_scores_gemma":[0.0008886013,0.0002355208,0.0003845794,0.003966471,0.0001458571,0.0007109789,0.0007136926,0.0004403312,0.00453916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001995989,"about_ca_system_score_gemma":0.00548663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3697578,"about_ca_topic_score_gemma":0.3817432,"domain_scores_codex":[0.9997036,0.00001288297,0.00003162084,0.00003377806,0.0001407408,0.000077405],"domain_scores_gemma":[0.9995356,0.00001078148,0.00006241025,0.00001989535,0.0002790221,0.00009229489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00020697,0.0001160519,0.2643996,0.001246419,0.0001071934,0.0002249182,0.001693711,0.0006290987,0.001443624,0.002343949,0.670291,0.05729749],"study_design_scores_gemma":[0.00002920473,0.00003837126,0.8589433,0.000118403,0.00003257234,0.0001193776,0.0008437153,0.0005211137,0.0004207417,0.0001254469,0.1387853,0.00002247304],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1452082,0.002147389,0.0004315752,0.000966744,0.0004068116,0.0006127571,0.7803621,0.0005167328,0.06934775],"genre_scores_gemma":[0.2495092,0.005150171,0.001548794,0.0006133184,0.0001467654,0.001337135,0.6663604,0.00008707096,0.07524719],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3697578,"threshold_uncertainty_score":0.7352111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02397523990736129,"score_gpt":0.3595679501930116,"score_spread":0.3355927102856504,"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."}}