{"id":"W7061736292","doi":"","title":"Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA): Spatial Analysis Framework","year":2017,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Advanced Power Generation Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spatial analysis; Statistic; Geographic information system; Road traffic; Poison control; Regression analysis; Spatial ecology; Common spatial pattern","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007689214,0.0004947442,0.0003126307,0.007240143,0.0009180103,0.002273321,0.0006737367,0.0002516338,0.001590327],"category_scores_gemma":[0.003216646,0.0001798081,0.0006592451,0.009222314,0.0007904668,0.0007345824,0.001501903,0.0002567642,0.0001368165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006116039,"about_ca_system_score_gemma":0.005301495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6574433,"about_ca_topic_score_gemma":0.7220169,"domain_scores_codex":[0.9991705,0.00024589,0.00006909523,0.0001216245,0.0002930388,0.00009983512],"domain_scores_gemma":[0.9987848,0.0003045469,0.0003503382,0.0000737398,0.0003836942,0.0001029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007062283,0.00005199699,0.8462884,0.0004887202,0.0003633738,0.0007870364,0.005047407,0.04009043,0.001140894,0.03050783,0.005209874,0.06995348],"study_design_scores_gemma":[0.00000741138,0.00009283652,0.8854834,0.0001945747,0.0001977055,0.0004351922,0.01967783,0.07351489,0.0005173183,0.005604157,0.01421777,0.00005697058],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8546324,0.003601176,0.08943626,0.00200049,0.00006771215,0.0005585465,0.01731524,0.00038897,0.03199914],"genre_scores_gemma":[0.9800015,0.0006745983,0.01641144,0.00001780497,0.00001587576,0.0000931885,0.001566983,0.000009471827,0.00120904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3425567,"threshold_uncertainty_score":0.6891481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173268844278015,"score_gpt":0.326600322892949,"score_spread":0.3048676344501688,"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."}}