{"id":"W4229714881","doi":"10.31219/osf.io/6vp8j","title":"A global assessment of street network sprawl","year":2020,"lang":"en","type":"preprint","venue":"OSF Preprints (OSF Preprints)","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Urban sprawl; Geography; Street network; Walkability; Economic geography; Regional science; Urban planning; Cartography; Transport engineering; Built environment; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009488477,0.0003911417,0.0002627333,0.005434758,0.0002864611,0.001391504,0.0002959596,0.0003240238,0.001686395],"category_scores_gemma":[0.004732992,0.000136106,0.000438036,0.00731506,0.0006853297,0.002406485,0.001575814,0.0003736802,0.000234661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005558859,"about_ca_system_score_gemma":0.0002329625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002740005,"about_ca_topic_score_gemma":0.004967347,"domain_scores_codex":[0.9993582,0.0001599071,0.00006759106,0.0001629775,0.0001871937,0.00006416486],"domain_scores_gemma":[0.99639,0.0008629283,0.001171871,0.0005410166,0.0008286008,0.0002054705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006889826,0.00003627935,0.8677489,0.0002882761,0.000359607,0.0001480394,0.001764595,0.03691255,0.002332568,0.01921779,0.005222346,0.06589998],"study_design_scores_gemma":[0.000007383739,0.0001291197,0.9098962,0.00009870519,0.0001045715,0.0003582698,0.00382592,0.04642639,0.00159882,0.01295647,0.02454931,0.00004884444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418094,0.0004573397,0.02777028,0.0003098395,0.00002760174,0.0000787167,0.01342869,0.0003291207,0.015789],"genre_scores_gemma":[0.9847183,0.000173775,0.007245562,0.00003011497,0.00001426658,0.00005770504,0.007248634,0.00004275024,0.0004688191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005434758,"threshold_uncertainty_score":0.00564158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02919105899323782,"score_gpt":0.3341617691845222,"score_spread":0.3049707101912844,"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."}}