{"id":"W4244447481","doi":"10.32920/ryerson.14652519.v1","title":"The role of parking pricing and parking availability on travel mode choice","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Business; Mode choice; Transport engineering; Willingness to pay; Mode (computer interface); Parking guidance and information; Environmental economics; Marketing; Computer science; Economics; Public transport; Engineering; Microeconomics","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"],"consensus_categories":[],"category_scores_codex":[0.001163745,0.0003332974,0.0005247815,0.0001175096,0.0001574212,0.0002510464,0.0004396734,0.0002846208,0.00002287247],"category_scores_gemma":[0.0003619377,0.0002661039,0.0001300399,0.000164268,0.00008884694,0.00005297184,0.0005301984,0.001055666,0.000004439746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002046761,"about_ca_system_score_gemma":0.00008888174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001008831,"about_ca_topic_score_gemma":0.0006709535,"domain_scores_codex":[0.9975854,0.0002019486,0.0006149343,0.0005389574,0.0005776223,0.0004811632],"domain_scores_gemma":[0.997382,0.001272673,0.0001065487,0.001018056,0.0001221912,0.00009857224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001001783,0.0002192072,0.2771783,0.008951252,0.001927946,0.00003150015,0.01137199,0.365091,0.1256578,0.002061924,0.0007234006,0.2066855],"study_design_scores_gemma":[0.0003660168,0.00003868981,0.07544741,0.002040403,0.00005371169,0.00001272379,0.002189656,0.8279002,0.08162779,0.0006270091,0.00888197,0.0008144214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9563282,0.004074585,0.00194718,0.00003315762,0.0006476589,0.0006271668,0.000009366853,0.0001991467,0.0361335],"genre_scores_gemma":[0.9986943,0.0003201197,0.0004184711,0.000006138629,0.0002120836,0.00009209103,0.000007751033,0.00006894419,0.000180115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4628092,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947012161436792,"score_gpt":0.2689418523731613,"score_spread":0.2494717307587934,"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."}}