{"id":"W7124178004","doi":"10.37665/leifnko27953","title":"“Optoelectronic Fingerprint Sensor for Mobile Phones”","year":2002,"lang":"","type":"article","venue":"Specialized and Legacy Electronics Manufacturing Conferences","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Native Health Society","funders":"","keywords":"Fingerprint (computing); Microprocessor; Fingerprint recognition; Mobile phone; Biometrics; Mobile device; Chip; Cursor (databases)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002685061,0.0002773344,0.0002722491,0.0003684482,0.0002350233,0.0005318705,0.0004719705,0.0008278736,0.004134838],"category_scores_gemma":[0.0004937662,0.0001770737,0.0001503253,0.0002826758,0.0002009133,0.0006373798,0.0002844756,0.0003258885,0.001599693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003133597,"about_ca_system_score_gemma":0.0002578121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002612202,"about_ca_topic_score_gemma":0.0005534002,"domain_scores_codex":[0.9995888,0.00004901636,0.00001824498,0.00006955166,0.0002429567,0.00003143993],"domain_scores_gemma":[0.9997998,0.0000254706,0.00003011692,0.00001965889,0.0001084882,0.0000164772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000324192,0.00005529181,0.00127367,0.0003267097,0.00002121221,0.0003158544,0.00006112966,0.0005817045,0.8119818,0.004259711,0.01174575,0.169053],"study_design_scores_gemma":[0.00005626054,0.0006372908,0.003854702,0.00008736469,0.00006188588,0.00264717,0.00006039634,0.01470957,0.9001254,0.001039747,0.07666361,0.00005661383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3300533,0.03242405,0.5383281,0.00492373,0.003612862,0.0006001581,0.001747994,0.005398935,0.08291086],"genre_scores_gemma":[0.769601,0.003828332,0.1750065,0.001394917,0.0002307877,0.0001666514,0.0005057516,0.00006395189,0.049202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004134838,"threshold_uncertainty_score":0.01383239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03064010971664423,"score_gpt":0.261544606042661,"score_spread":0.2309044963260168,"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."}}