{"id":"W4389451886","doi":"10.3390/computers12120255","title":"A Systematic Review of Using Machine Learning and Natural Language Processing in Smart Policing","year":2023,"lang":"en","type":"review","venue":"Computers","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Mitacs","keywords":"Law enforcement; Computer science; Artificial intelligence; Process (computing); Enforcement; Computer security; Machine learning; Data science; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0004460623,0.0002814292,0.001891866,0.0002828125,0.00004020046,0.000142457,0.0005451583,0.00006055098,1.987431e-7],"category_scores_gemma":[0.0001018318,0.0002130167,0.0001915318,0.0009933666,0.00003955417,0.0002363188,0.0005935559,0.0003109345,0.000005733282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006644985,"about_ca_system_score_gemma":0.00008954914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001007427,"about_ca_topic_score_gemma":0.0000124795,"domain_scores_codex":[0.9982366,0.000163032,0.000789424,0.0003447197,0.0002233235,0.000242891],"domain_scores_gemma":[0.9989527,0.0001498331,0.0005519254,0.0002561246,0.0000365123,0.00005285741],"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":[6.774911e-8,0.000003943149,0.000002029777,0.7698171,0.00001842769,0.00002764334,0.0001681331,0.000001293532,5.518674e-8,0.0000979027,0.000002667484,0.2298608],"study_design_scores_gemma":[0.00004532283,0.000009967207,7.277656e-7,0.9586851,0.0001424572,0.0001477805,0.000007650777,0.03979689,1.092688e-7,0.00001334314,0.0009345384,0.0002161169],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001157303,0.9966568,0.002472211,0.000007295379,0.0001836286,0.0005410336,0.000002154123,0.0000915447,0.00003372113],"genre_scores_gemma":[0.00004696103,0.9967608,0.002972363,0.00006753948,0.00002491872,0.00001068302,0.00001380302,0.00002599896,0.00007695342],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.2296446,"threshold_uncertainty_score":0.8686569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771198561912017,"score_gpt":0.3150183600637176,"score_spread":0.2873063744445974,"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."}}