{"id":"W7099110400","doi":"","title":"Report on Public Health and Urban Sprawl in Ontario","year":2005,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Urban sprawl; Public health; Population; Urban planning; Work (physics)","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":[0.0006267059,0.000270547,0.000308202,0.002579323,0.002223558,0.001055208,0.0005538624,0.0005374718,0.006045404],"category_scores_gemma":[0.002027919,0.0002610238,0.000612107,0.005008982,0.000501255,0.0004524519,0.001497507,0.0006503868,0.0004657209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0223381,"about_ca_system_score_gemma":0.05806541,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939327,"about_ca_topic_score_gemma":0.9971414,"domain_scores_codex":[0.9990089,0.00007766736,0.000100431,0.00005171003,0.000450214,0.0003111106],"domain_scores_gemma":[0.9971813,0.0001621854,0.0003773395,0.00006894484,0.001637981,0.0005723313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002833904,0.00008262569,0.9089609,0.0004798205,0.000138207,0.0007339153,0.004056414,0.0005186627,0.0004158809,0.0008787441,0.06516785,0.01828361],"study_design_scores_gemma":[0.00001629583,0.00004442764,0.9608709,0.00004900225,0.00004610369,0.00006874017,0.006349405,0.0001982902,0.0001454805,0.00005819716,0.03213733,0.00001583606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6943255,0.004951496,0.0006463864,0.01854985,0.0004043486,0.0005807924,0.202288,0.0002505494,0.07800319],"genre_scores_gemma":[0.8851576,0.005595285,0.000698595,0.001173473,0.0001331454,0.0003039716,0.03853112,0.00003307547,0.06837367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0223381,"threshold_uncertainty_score":0.162075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03857130004790331,"score_gpt":0.2415963209316387,"score_spread":0.2030250208837354,"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."}}