{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001009934,0.0004589907,0.0007538963,0.00009405155,0.0001049163,0.001231297,0.0005383971,0.0005092505,0.0004650257],"category_scores_gemma":[0.0002035837,0.0004938124,0.000305792,0.00007742,0.00003380342,0.0004314675,0.0005492753,0.0004623423,0.0000153312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009193463,"about_ca_system_score_gemma":0.0002087028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004484267,"about_ca_topic_score_gemma":0.0005672117,"domain_scores_codex":[0.9971443,0.0001079041,0.000744984,0.0006826136,0.0005772499,0.0007429579],"domain_scores_gemma":[0.9981504,0.000424892,0.0001084752,0.0009181857,0.0002355877,0.0001624672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002613848,0.0006889346,0.01553311,0.05386461,0.01200611,0.0005570904,0.01180442,0.09832178,0.3092395,0.001499818,0.1962653,0.299958],"study_design_scores_gemma":[0.006924269,0.0001280773,0.005269808,0.008464477,0.0004079165,0.00006505234,0.01077051,0.6972641,0.09752563,0.0003494481,0.167643,0.005187714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4729404,0.01108145,0.2519079,0.00008422763,0.02152523,0.004598464,0.00006296468,0.002383912,0.2354154],"genre_scores_gemma":[0.9813133,0.0001165857,0.01503084,0.000029179,0.000990159,0.0008504019,0.0002009074,0.0001877116,0.001280854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5989423,"threshold_uncertainty_score":0.9998055,"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."}}