{"id":"W2039401290","doi":"10.1109/sadfe.2010.20","title":"Digital Records Forensics: Ensuring Authenticity and Trustworthiness of Evidence Over Time","year":2010,"lang":"en","type":"article","venue":"","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Digital forensics; Workflow; Digital evidence; Trustworthiness; Computer forensics; Computer science; Domain (mathematical analysis); Data science; Work (physics); Network forensics; Computer security; World Wide Web; Internet privacy; Engineering; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.03938645,0.0006498394,0.0008358124,0.008538681,0.005808529,0.01572378,0.003325276,0.00406989,0.003048218],"category_scores_gemma":[0.09190036,0.0008888918,0.0006182949,0.005439123,0.009742456,0.01747696,0.0104468,0.002631922,0.0019852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003720984,"about_ca_system_score_gemma":0.0186049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01122659,"about_ca_topic_score_gemma":0.008596422,"domain_scores_codex":[0.9587005,0.01631221,0.004070018,0.003126139,0.01657119,0.001219932],"domain_scores_gemma":[0.8774543,0.04846893,0.01485824,0.03084635,0.0257464,0.002625736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002392267,0.0002063074,0.01706111,0.001591576,0.0001032801,0.001303833,0.02009867,0.00406083,0.007209807,0.2092995,0.01465526,0.7241706],"study_design_scores_gemma":[0.0001567558,0.0004469217,0.01655318,0.005282864,0.0002712344,0.006485969,0.03214699,0.01903442,0.03424757,0.3289627,0.555942,0.000469368],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09738743,0.01179388,0.7728274,0.0349585,0.0009308648,0.001375286,0.001345839,0.001677623,0.07770322],"genre_scores_gemma":[0.5970876,0.01130154,0.3715869,0.00179843,0.0006610802,0.0004062251,0.001035826,0.000320029,0.01580237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03938645,"threshold_uncertainty_score":0.208298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02133203309839773,"score_gpt":0.2348229164674742,"score_spread":0.2134908833690765,"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."}}