{"id":"W3194325189","doi":"10.32920/ryerson.14644152.v1","title":"Assessing Toronto's minimums parking requirements for condominiums","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Work (physics); Process (computing); Order (exchange); Transport engineering; Business; Policy development; Set (abstract data type); Computer science; Engineering; Finance","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":[0.004064936,0.0002341836,0.0002176955,0.002326267,0.001900079,0.002624396,0.001484743,0.0004835551,0.005220448],"category_scores_gemma":[0.01724363,0.0003460663,0.0002756481,0.002808984,0.001102876,0.001177829,0.001196153,0.0004671441,0.0004281982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02965585,"about_ca_system_score_gemma":0.03097595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7536671,"about_ca_topic_score_gemma":0.9232914,"domain_scores_codex":[0.9965012,0.0003937479,0.0002226931,0.0002206672,0.002273394,0.0003882466],"domain_scores_gemma":[0.9799609,0.005247483,0.002170667,0.0006708545,0.01053612,0.001413969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004484224,0.0001569732,0.688857,0.002861614,0.00008680629,0.002092511,0.09657943,0.01338757,0.01540659,0.02585027,0.02302009,0.1312528],"study_design_scores_gemma":[0.0000241391,0.0002335423,0.8720209,0.0003700354,0.0000675159,0.0002981856,0.04528271,0.004690656,0.006116895,0.0007674862,0.07004577,0.00008205591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572542,0.0007220242,0.003073705,0.00112783,0.00003419573,0.0001981297,0.002850775,0.0001150705,0.03462416],"genre_scores_gemma":[0.9903511,0.000322003,0.003863511,0.00003719998,0.000006016342,0.0001037344,0.001317678,0.00002088233,0.003977873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2463329,"threshold_uncertainty_score":0.4955671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1004455996731572,"score_gpt":0.3762701639841249,"score_spread":0.2758245643109677,"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."}}