{"id":"W3182704732","doi":"","title":"The Proactive and Reactive Digital Forensics Investigation Process : A Systematic Literature Review","year":2011,"lang":"en","type":"article","venue":"International Journal of Security and Its Applications","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Digital forensics; Process (computing); Computer science; Digital evidence; Computer forensics; Automation; Component (thermodynamics); Data science; Systematic review; Computer security; Engineering","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":[0.06752945,0.001306131,0.004370263,0.03248463,0.001455998,0.00392138,0.002615179,0.002384173,0.002522143],"category_scores_gemma":[0.1625756,0.001323885,0.002573427,0.02114023,0.001851451,0.007348435,0.002875481,0.0008815293,0.0006173986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006213423,"about_ca_system_score_gemma":0.0358175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005107586,"about_ca_topic_score_gemma":0.01766551,"domain_scores_codex":[0.9317602,0.03729579,0.01753721,0.002734834,0.009962237,0.0007097585],"domain_scores_gemma":[0.8093958,0.1265874,0.02239193,0.003838456,0.03625279,0.001533542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004156226,0.0002202239,0.007583132,0.5467891,0.001823919,0.001005925,0.01112202,0.0007053839,0.00132478,0.002756643,0.005498133,0.4207552],"study_design_scores_gemma":[0.000396059,0.00116575,0.01690097,0.862418,0.01140508,0.001858951,0.02577471,0.0009225789,0.002128753,0.003324777,0.07349777,0.0002066886],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03002388,0.9279643,0.01787215,0.003742848,0.0003751011,0.01443752,0.002239016,0.0001015696,0.003243669],"genre_scores_gemma":[0.1789828,0.7040458,0.09049205,0.002174787,0.00014366,0.02096524,0.001960208,0.00004438942,0.001191063],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.06752945,"threshold_uncertainty_score":0.3571342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267989284098777,"score_gpt":0.2378670376515301,"score_spread":0.2251871448105423,"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."}}