{"id":"W4389431965","doi":"10.3390/safety9040088","title":"Linking Deployment Outcomes to Program Impacts for Mobile Photo Enforcement","year":2023,"lang":"en","type":"article","venue":"Safety","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Software deployment; Survivability; Enforcement; Duration (music); Collision; Transport engineering; Law enforcement; Computer security; Computer science; Engineering; Computer network; Political science; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002011415,0.000175674,0.0002005059,0.00008771146,0.0001045978,0.00002417375,0.0001392991,0.00006633929,0.00006033911],"category_scores_gemma":[0.00001216801,0.000149024,0.0001237453,0.0002607936,0.000008946603,0.00005131352,0.00005511936,0.00008019072,0.0002361119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001329612,"about_ca_system_score_gemma":0.00001879817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009426272,"about_ca_topic_score_gemma":0.00002915296,"domain_scores_codex":[0.998876,0.00000618673,0.0002681075,0.0001816734,0.0001680123,0.0005000483],"domain_scores_gemma":[0.9995098,0.00006298196,0.00001737079,0.0002262981,0.00002280454,0.0001607054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009224637,0.00007707223,0.006637583,0.0003578345,0.0002157841,0.000008202604,0.001972892,0.5485464,0.0005890846,0.0009034583,0.006876151,0.4337233],"study_design_scores_gemma":[0.001410053,0.0004036267,0.1000807,0.0001321183,0.00004066136,0.000001866542,0.0003604686,0.04640698,0.002473234,0.00008545571,0.8480367,0.0005681335],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.924364,0.0003347859,0.03095205,0.0005344082,0.003826296,0.01068119,0.000298819,0.01345359,0.01555489],"genre_scores_gemma":[0.9949,0.00008042748,0.003052049,0.000107159,0.0001041355,0.001027024,0.0000740358,0.00006207088,0.0005930336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8411606,"threshold_uncertainty_score":0.6077023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507548388889955,"score_gpt":0.2854529027711348,"score_spread":0.2703774188822353,"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."}}