{"id":"W4412930278","doi":"10.1016/j.fsidi.2025.301972","title":"Tool type identification for forensic digital document examination","year":2025,"lang":"en","type":"article","venue":"Forensic Science International Digital Investigation","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"University of Winnipeg","keywords":"Identification (biology); Forensic science; Digital forensics; Forensic identification; Forensic examination; Computer science; Type (biology); Digital evidence; Data science; Computer security; Engineering; Forensic engineering; Geography; Archaeology; Biology; Paleontology","routes":{"ca_aff":true,"ca_fund":true,"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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005223515,0.0002235424,0.000155576,0.0005615539,0.0002786,0.00460119,0.001427404,0.00006824046,0.000005302039],"category_scores_gemma":[0.001283323,0.0002163505,0.000104912,0.001681517,0.0007727223,0.008732472,0.000393342,0.00008681328,0.0001370049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709435,"about_ca_system_score_gemma":0.0003802453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004954197,"about_ca_topic_score_gemma":0.000002487232,"domain_scores_codex":[0.9973528,0.000009386598,0.000576154,0.000755,0.0009348245,0.0003718134],"domain_scores_gemma":[0.9975424,0.0001333356,0.0002465667,0.0004951933,0.001466352,0.0001161014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009007191,0.00003470172,0.0008846769,0.00001041964,0.00001967106,8.75437e-7,0.0001487279,0.0001106423,0.001041447,0.6446354,0.002351657,0.3507528],"study_design_scores_gemma":[0.0005691791,0.0001546018,0.02959044,0.0001182712,0.00001313766,0.00001574869,0.0001046443,0.07110237,0.04169426,0.8477047,0.008485136,0.0004474791],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5921513,0.00002981974,0.3441536,0.003333903,0.007354804,0.0009204059,0.00009520951,0.0004240611,0.05153687],"genre_scores_gemma":[0.9872565,0.000001888262,0.005270398,0.0005042888,0.0001079644,0.00006497386,0.0003024872,0.00001028213,0.00648117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3951052,"threshold_uncertainty_score":0.9964321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01647634175532159,"score_gpt":0.2632042401191722,"score_spread":0.2467278983638506,"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."}}