{"id":"W4416955489","doi":"10.2139/ssrn.5749902","title":"Visibility and Retail Demand: Evidence from Bike Share","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Visibility; Signage; Taxis; Measure (data warehouse); Shopping mall","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":[0.0008560629,0.0004103146,0.0006877892,0.001886792,0.0007054335,0.002959976,0.0008930239,0.001560725,0.01852733],"category_scores_gemma":[0.01406924,0.0005091388,0.0008384123,0.003985907,0.00116067,0.002934056,0.001671743,0.001395575,0.002667757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004773417,"about_ca_system_score_gemma":0.0004095516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02783386,"about_ca_topic_score_gemma":0.02261211,"domain_scores_codex":[0.9990096,0.0002834912,0.00008191235,0.0001996833,0.0002095061,0.0002158183],"domain_scores_gemma":[0.9637462,0.01944148,0.01056421,0.00218346,0.002079708,0.001984865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001968809,0.0005227093,0.9843128,0.0001339923,0.0004661429,0.0002625194,0.00124405,0.0005466935,0.000498476,0.001665462,0.001214713,0.007163618],"study_design_scores_gemma":[0.00005948273,0.000270785,0.9905563,0.00004619676,0.0002379867,0.0001454385,0.003780941,0.000872859,0.0003135983,0.001948032,0.001738092,0.00003029358],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922883,0.0006644342,0.0001970207,0.0003013103,0.000008713389,0.000006357397,0.00107417,0.000007364694,0.005452395],"genre_scores_gemma":[0.9978909,0.0002179862,0.00003350309,0.00002642483,0.00001239912,0.000003179193,0.0007747179,0.000006859465,0.001034135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02783386,"threshold_uncertainty_score":0.06198007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088408202669256,"score_gpt":0.2378010370358578,"score_spread":0.2069169550091653,"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."}}