{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008841059,0.0007855337,0.0009413419,0.0007610285,0.001185079,0.003430866,0.00140116,0.0004174598,0.001748653],"category_scores_gemma":[0.0001261269,0.0007906317,0.000389423,0.0007753223,0.0003712972,0.001064605,0.0003161265,0.0008699657,0.0001438006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003317011,"about_ca_system_score_gemma":0.0005831028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001778229,"about_ca_topic_score_gemma":0.0001838176,"domain_scores_codex":[0.9943005,0.0002614698,0.001061192,0.001761674,0.000698823,0.001916376],"domain_scores_gemma":[0.9972907,0.00046523,0.0006011489,0.0009646059,0.0002749992,0.0004033385],"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":[0.0001236215,0.0005808426,0.00004067825,0.0003298634,0.0003395287,0.00001038232,0.004793877,0.00002825753,0.0009009944,0.1248212,0.002514202,0.8655165],"study_design_scores_gemma":[0.002710639,0.001064861,0.0003214636,0.00008198112,0.0001459873,0.00005218375,0.0004402171,0.05034973,0.05726191,0.01202991,0.8741292,0.001411937],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5760674,0.1074553,0.2760735,0.008653098,0.008416747,0.006990916,0.0001532665,0.0009872287,0.01520244],"genre_scores_gemma":[0.9711661,0.02015786,0.001948642,0.0002791893,0.0008525205,0.0002028907,0.00002667068,0.0000453188,0.005320772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.871615,"threshold_uncertainty_score":0.9994544,"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."}}