{"id":"W4413103219","doi":"10.2139/ssrn.5368369","title":"Securing Forensic Data with Cryptographic Techniques","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Cryptography; Computer security; Computer science; Forensic science; Geography; Archaeology","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","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001238386,0.0004277324,0.0004148196,0.000396639,0.0002132043,0.00084712,0.005454332,0.0002120975,0.000001869005],"category_scores_gemma":[0.00002399506,0.0003346351,0.0001625434,0.0005343995,0.0001193375,0.0008975771,0.004549087,0.004916555,0.000006112743],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003990926,"about_ca_system_score_gemma":0.006024473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006486817,"about_ca_topic_score_gemma":0.0009530817,"domain_scores_codex":[0.9957526,0.00006079077,0.0004111689,0.000866105,0.0005673724,0.002341904],"domain_scores_gemma":[0.9971699,0.00004017247,0.0003484832,0.002111573,0.0002127128,0.0001171563],"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":[0.00001426282,0.00005126974,0.000178638,0.00004031148,0.0003475401,0.00002314587,0.00007106487,0.00002762459,0.000002855893,0.6799373,0.0005267104,0.3187793],"study_design_scores_gemma":[0.0001961497,0.0002279897,0.00004419639,0.0004553465,0.0000673949,0.0006748467,0.00007286128,0.001245873,0.0001935404,0.990063,0.006279722,0.0004790454],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003915655,0.004210646,0.9733216,0.001378791,0.0006836285,0.0003419103,0.00003947718,0.0005221193,0.01558619],"genre_scores_gemma":[0.8646402,0.01650532,0.111618,0.000961388,0.001459753,0.00006604329,0.0002249396,0.000114685,0.004409587],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8617036,"threshold_uncertainty_score":0.9999266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211950920423871,"score_gpt":0.2424698646118457,"score_spread":0.230350355407607,"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."}}