{"id":"W4379165195","doi":"10.1007/978-3-031-31746-0_8","title":"Disclosing the Impact of Micro-level Environmental Characteristics on Dockless Bikeshare Trip Volume: A Case Study of Ithaca","year":2023,"lang":"en","type":"book-chapter","venue":"The urban book series","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cycling; Built environment; Macro; Macro level; Micro level; Environmental impact assessment; Volume (thermodynamics); Geography; Computer science; Transport engineering; Engineering; Civil engineering; Forestry; Political science; Economic impact analysis","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":[0.0007401445,0.0002370463,0.0001844784,0.0006711496,0.004432195,0.004441747,0.00135157,0.001542404,0.01846845],"category_scores_gemma":[0.00399904,0.0002198167,0.0001866181,0.001485907,0.001197263,0.002499758,0.002519567,0.001293487,0.001327644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003172119,"about_ca_system_score_gemma":0.002794116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09756556,"about_ca_topic_score_gemma":0.2930131,"domain_scores_codex":[0.9994581,0.0002229915,0.00002333838,0.00005409434,0.0001459191,0.00009544173],"domain_scores_gemma":[0.9979568,0.001221263,0.0002914553,0.000192713,0.0001873122,0.0001504731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003560597,0.001591056,0.2964862,0.000494906,0.0000783433,0.037051,0.3056675,0.003347768,0.005777773,0.03197062,0.07212943,0.2450494],"study_design_scores_gemma":[0.00001916594,0.0006317231,0.2953726,0.0005293114,0.00007320177,0.005541889,0.5066291,0.003988564,0.002973168,0.003408448,0.1807094,0.0001234124],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8698774,0.0004381944,0.0006497045,0.002112032,0.00004583647,0.00008085676,0.0007628425,0.00004638548,0.1259867],"genre_scores_gemma":[0.9512208,0.0006488534,0.0007089804,0.0001429785,0.00001566558,0.00005714314,0.0002788029,0.00002281428,0.04690398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09756556,"threshold_uncertainty_score":0.1939954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04731296517550398,"score_gpt":0.289290213139432,"score_spread":0.2419772479639281,"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."}}