{"id":"W4389147933","doi":"10.1017/bjt.2023.11","title":"Biometric data's colonial imaginaries continue in Aadhaar's minimal data","year":2023,"lang":"en","type":"article","venue":"BJHS Themes","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"University of Cambridge; University of Oxford; University of Wisconsin-Madison; University of Pennsylvania","keywords":"Identity (music); Biometrics; Race (biology); Government (linguistics); Key (lock); Corporate governance; Computer science; Argument (complex analysis); Identification (biology); Sociology; Computer security; Law; Political science; Business; Linguistics; Gender studies; Aesthetics; Medicine; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.0004581099,0.0001536566,0.0001814702,0.0001139536,0.00009399955,0.00006629904,0.001226111,0.0001414454,0.00001934877],"category_scores_gemma":[0.0004115074,0.000149851,0.00004078232,0.0005459828,0.0002406872,0.00001205838,0.001561485,0.00008796877,0.00006096803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008419825,"about_ca_system_score_gemma":0.0001197093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001035703,"about_ca_topic_score_gemma":0.0002540865,"domain_scores_codex":[0.998568,0.00005532704,0.0002197268,0.0006450247,0.0001599997,0.0003519059],"domain_scores_gemma":[0.9981689,0.00004068251,0.00006521063,0.001619118,0.00004588796,0.00006022234],"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":[0.000220249,0.0002759966,0.05724173,0.00008149781,0.0002266257,0.00006062126,0.00144457,0.00001760023,0.3595713,0.0001761902,0.5595894,0.02109411],"study_design_scores_gemma":[0.001552162,0.0002312192,0.0612319,0.00001734936,0.0000438813,0.00001333614,0.00175651,0.001402695,0.03685606,0.0003072002,0.8960609,0.0005267297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932662,0.003320481,0.00005765897,0.0009776767,0.0003877461,0.0001913286,0.00085351,0.00003938906,0.0009060415],"genre_scores_gemma":[0.9899741,0.001610839,0.00116489,0.0001841573,0.0005262282,0.00001151164,0.004319218,0.00003051994,0.00217853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3364715,"threshold_uncertainty_score":0.6110746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04569052283723889,"score_gpt":0.323270976215167,"score_spread":0.2775804533779281,"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."}}