{"id":"W2321990935","doi":"10.1097/phh.0b013e318215a4c7","title":"Setting the Standards for Collecting Ethnicity Data in the Commonwealth of Massachusetts","year":2011,"lang":"en","type":"article","venue":"Journal of Public Health Management and Practice","topic":"Racial and Ethnic Identity Research","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smiths Detection (Canada)","funders":"","keywords":"Ethnic group; Commonwealth; Race (biology); Masking (illustration); Data collection; Directive; Population; Public health; Health equity; Medicine; Gerontology; Psychology; Computer science; Political science; Environmental health; Nursing; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1386326,0.0000541431,0.0001678162,0.000136125,0.0009649274,0.0001770233,0.0009170235,0.00003548218,0.00002383609],"category_scores_gemma":[0.01064552,0.00003268745,0.00003207794,0.0005850067,0.0001631471,0.001194124,0.000182804,0.0004072695,2.962847e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001301405,"about_ca_system_score_gemma":0.001078474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007073961,"about_ca_topic_score_gemma":0.007750816,"domain_scores_codex":[0.9938805,0.003950867,0.0005663625,0.0001094869,0.001097236,0.0003955507],"domain_scores_gemma":[0.9948192,0.003522956,0.0008716529,0.0002416775,0.0004363417,0.000108199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005115747,0.0005928745,0.01392706,0.0008508209,0.0002460869,0.00002771606,0.2779658,0.000002072885,8.582493e-7,0.07586811,0.1561383,0.4738686],"study_design_scores_gemma":[0.0004458596,0.0001854105,0.01486034,0.00004804025,0.00002650476,0.000008714273,0.158729,0.00005687728,1.841357e-7,0.002155572,0.8234412,0.0000422566],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01635924,0.003522837,0.01052959,0.8272083,0.0006565067,0.002077518,0.00005443757,0.00001101208,0.1395806],"genre_scores_gemma":[0.9697432,0.01367618,0.008688133,0.006514387,0.0005715768,0.00001636132,0.000004390207,0.00001260569,0.0007731964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9533839,"threshold_uncertainty_score":0.999538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4857837406111641,"score_gpt":0.5289567539179686,"score_spread":0.04317301330680445,"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."}}