{"id":"W4403534381","doi":"10.1109/codit62066.2024.10708215","title":"FingFor: a Deep Learning Tool for Biometric Forensics","year":2024,"lang":"en","type":"article","venue":"","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton; Université Laval","funders":"","keywords":"Biometrics; Computer science; Network forensics; Computer forensics; Deep learning; Artificial intelligence; Digital forensics; Computer security","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":[0.001021325,0.0009619417,0.0004555866,0.001255266,0.0004038792,0.001109279,0.002053233,0.001457726,0.01292685],"category_scores_gemma":[0.002987147,0.0005221567,0.0008247714,0.0006866522,0.0004515415,0.001854907,0.002487774,0.001822389,0.003986009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007718053,"about_ca_system_score_gemma":0.0008586666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002851779,"about_ca_topic_score_gemma":0.005035191,"domain_scores_codex":[0.9996896,0.00005807794,0.00001764906,0.00007084142,0.000120586,0.0000433268],"domain_scores_gemma":[0.9994876,0.0002235318,0.00005043927,0.00009377861,0.0001040909,0.00004049069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005406443,0.0002898874,0.002746161,0.0004162925,0.0003323953,0.0004127268,0.0001499877,0.1284778,0.01665547,0.01785179,0.0908734,0.7412535],"study_design_scores_gemma":[0.00003697498,0.00008628728,0.000506833,0.0000666066,0.00002815415,0.0002499228,0.00002487042,0.9426528,0.01186338,0.01594884,0.02850277,0.00003252719],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009721,0.0008903513,0.9312948,0.0006749854,0.0002184236,0.0001047543,0.002113978,0.050478,0.004503705],"genre_scores_gemma":[0.2562365,0.001779875,0.7080845,0.001328465,0.0001392489,0.0005303307,0.007598659,0.004126593,0.02017579],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01292685,"threshold_uncertainty_score":0.0432446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314383854000488,"score_gpt":0.237263902062401,"score_spread":0.2241200635223962,"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."}}