{"id":"W4211131003","doi":"10.1177/03611981221076848","title":"Internet-of-Things System to Protect Police Officers From Collisions While on Duty on the Roadway","year":2022,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"AUG Signals (Canada); York University","funders":"","keywords":"Officer; Computer security; Work (physics); Collision; Duty; The Internet; Transport engineering; Engineering; Computer science; Risk analysis (engineering); Business; Law","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":[0.0004252756,0.0005131226,0.0002543719,0.0007234138,0.0004827178,0.0004754272,0.0007704422,0.0005981791,0.003049906],"category_scores_gemma":[0.0009118007,0.0001533485,0.0004490699,0.0003651583,0.0001811484,0.0008634659,0.0006017788,0.000291099,0.001278522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002929589,"about_ca_system_score_gemma":0.0004542308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002600052,"about_ca_topic_score_gemma":0.004150674,"domain_scores_codex":[0.9997742,0.00004593698,0.00001954976,0.00003700119,0.00008754004,0.00003573961],"domain_scores_gemma":[0.9995698,0.0000918427,0.0000490073,0.00006678666,0.0001855863,0.00003704349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001191328,0.001057956,0.0500531,0.001389207,0.0004954297,0.002235266,0.001267405,0.06001007,0.07029133,0.01264458,0.05406152,0.7453027],"study_design_scores_gemma":[0.0003033032,0.0022542,0.04252158,0.0006049232,0.0007294512,0.003556737,0.002734492,0.7266321,0.08338798,0.02002243,0.1169626,0.0002902249],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2595772,0.001050861,0.670298,0.002265484,0.0009916086,0.001366303,0.001609316,0.01420785,0.04863346],"genre_scores_gemma":[0.923065,0.0004890842,0.06523892,0.0005168375,0.00006022942,0.0003236584,0.0006054779,0.00008964501,0.009611106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003049906,"threshold_uncertainty_score":0.01020294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06865264579008823,"score_gpt":0.3139470814573775,"score_spread":0.2452944356672893,"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."}}