{"id":"W2102933892","doi":"10.24908/ss.v3i1.3318","title":"Photographing Fingerprints: Data Collection and State Surveillance","year":2002,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Photography and Visual Culture","field":"Arts and Humanities","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Law enforcement; Identification (biology); Fingerprint (computing); Photography; State (computer science); Computer security; Law; Computer science; Sociology; Political science; Visual arts; Art; Algorithm","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":[0.0005398523,0.0002239766,0.0002636133,0.0000362234,0.0007874399,0.0003067699,0.0003016659,0.00006602717,0.0007199472],"category_scores_gemma":[0.0000542381,0.0001982884,0.0001374915,0.0002062667,0.0003663251,0.0003950496,0.0001505236,0.0002622003,0.00002206031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002105573,"about_ca_system_score_gemma":0.000009286893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007869875,"about_ca_topic_score_gemma":0.004520304,"domain_scores_codex":[0.9985538,0.00009348518,0.0002433543,0.0005186723,0.0002247858,0.0003659023],"domain_scores_gemma":[0.9990402,0.0001139112,0.0001225541,0.0005000191,0.0001350054,0.00008830585],"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":[0.00008070627,0.0004214855,0.1681484,0.0003329281,0.0006395704,0.000009296257,0.2159797,0.000008390905,0.001912893,0.002095606,0.5984385,0.01193253],"study_design_scores_gemma":[0.001225663,0.0001398309,0.03693901,0.00005714961,0.00001678239,0.000009617517,0.007832306,0.008947881,0.0001374414,0.0007125217,0.9430057,0.0009760562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795606,0.004974683,0.0001547139,0.0003942646,0.001275869,0.0004479627,0.0007993458,0.0004816719,0.01191087],"genre_scores_gemma":[0.9935575,0.003933322,0.0001082339,0.0004683988,0.0003487331,0.00001602043,0.00009808288,0.00002506188,0.001444617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3445672,"threshold_uncertainty_score":0.8085967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06183339061940196,"score_gpt":0.2552542954156602,"score_spread":0.1934209047962582,"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."}}