{"id":"W4252710879","doi":"10.1016/s0969-4765(09)70199-7","title":"USA joins biometric data sharing initiative","year":2009,"lang":"en","type":"article","venue":"Biometric Technology Today","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biometrics; Homeland security; Joins; Join (topology); Political science; Computer security; Business; Computer science; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001704405,0.000198846,0.000291041,0.01223158,0.0007995803,0.0001530536,0.004118036,0.0006190275,0.000234047],"category_scores_gemma":[0.01029274,0.0002006448,0.00005030149,0.04522189,0.0004995762,0.0009353219,0.001614231,0.0004165519,0.0003923297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002689197,"about_ca_system_score_gemma":0.0001685511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054225,"about_ca_topic_score_gemma":0.0002796643,"domain_scores_codex":[0.9974518,0.00009463249,0.0003606617,0.0008921511,0.0005115236,0.0006892607],"domain_scores_gemma":[0.997497,0.0001557143,0.00022078,0.001834334,0.0001475844,0.0001445743],"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":[0.00002399194,0.0006546667,0.029986,0.00001667242,0.00009720182,0.00005273611,0.0009308492,1.350872e-7,0.00380231,0.06593926,0.02155839,0.8769378],"study_design_scores_gemma":[0.001321845,0.0007566842,0.07755878,0.00005177382,0.0001015688,0.00002799055,0.003032453,0.0001714253,0.007359747,0.1187997,0.7897289,0.001089121],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6347888,0.02748309,0.06736515,0.113718,0.006733513,0.00458314,0.001625436,0.008809279,0.1348936],"genre_scores_gemma":[0.9940608,0.0009651678,0.004040073,0.0003119702,0.0002764056,0.00001628416,0.0000988532,0.00001231769,0.0002181838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8758487,"threshold_uncertainty_score":0.998964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227399437855384,"score_gpt":0.3667998879556539,"score_spread":0.2440599441701155,"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."}}