{"id":"W4389371651","doi":"10.17072/2619-0648-2022-3-116-127","title":"DIGITAL VIDEO IMAGES IN FORENSIC IDENTIFICATION","year":2022,"lang":"en","type":"article","venue":"Ex Jure","topic":"Security, Politics, and Digital Transformation","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Computer science; Identification (biology); Relevance (law); Reliability (semiconductor); Digital video; Artificial intelligence; Software; Mode (computer interface); Digital forensics; Multimedia; Computer vision; Frame (networking); Human–computer interaction; Computer security; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00121627,0.0004720976,0.0002678879,0.004291944,0.0008209986,0.002486569,0.0005711445,0.00196864,0.01083272],"category_scores_gemma":[0.002964793,0.0001519827,0.0002054186,0.002492121,0.002334739,0.002592757,0.001230178,0.0009986559,0.002637957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021269,"about_ca_system_score_gemma":0.000747962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001355522,"about_ca_topic_score_gemma":0.001447385,"domain_scores_codex":[0.9990383,0.0004576746,0.00005883256,0.00008097065,0.0003049274,0.0000593855],"domain_scores_gemma":[0.9983247,0.0009123597,0.0001534431,0.0001082206,0.0004298007,0.00007156005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001400691,0.00008472861,0.003577737,0.001357221,0.00002924804,0.002105485,0.00169782,0.001597975,0.003511208,0.3364366,0.04253697,0.606925],"study_design_scores_gemma":[0.00001710818,0.0001454766,0.006809101,0.003408988,0.00005378752,0.008250142,0.003447537,0.004202854,0.005410139,0.1062457,0.8619455,0.00006379269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03168676,0.4294288,0.1091374,0.01701788,0.01141057,0.0002420493,0.000545062,0.0003654341,0.4001659],"genre_scores_gemma":[0.538548,0.2183186,0.09279785,0.006003137,0.009507713,0.0002072577,0.0005429419,0.000142019,0.1339326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01083272,"threshold_uncertainty_score":0.03623909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986181625496826,"score_gpt":0.295707677231351,"score_spread":0.2758458609763828,"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."}}