{"id":"W3028428492","doi":"10.1287/trsc.2019.0950","title":"Integrating Resource Management in Service Network Design for Bike-Sharing Systems","year":2020,"lang":"en","type":"article","venue":"Transportation Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Computer science; Service (business); Operations research; Network planning and design; Redistribution (election); Resource allocation; Heuristic; Level of service; Transport engineering; Computer network; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000489878,0.0001052758,0.0001157102,0.0001136881,0.0001102879,0.00006309392,0.0002619038,0.00002970622,0.000007852947],"category_scores_gemma":[0.000008795055,0.0001145723,0.00002209363,0.002215964,0.00003414191,0.0003086671,0.000001727914,0.0000905154,0.000005883024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004276606,"about_ca_system_score_gemma":0.00002563726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001936553,"about_ca_topic_score_gemma":0.0001411075,"domain_scores_codex":[0.9988366,0.000005937784,0.0004093801,0.0002703964,0.0002207546,0.0002569479],"domain_scores_gemma":[0.9996191,0.00004092963,0.00003902128,0.0001233503,0.00009792167,0.00007962588],"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":[0.00001024346,0.000005447267,0.001132665,0.0001457866,0.000005568466,0.000001612395,0.00261307,0.9692602,0.001026159,0.02506753,0.00007169125,0.0006599839],"study_design_scores_gemma":[0.0006147086,0.00002573982,0.03688534,0.0001081573,0.00002153731,2.824748e-7,0.002882055,0.9535801,0.0006010951,0.0003414697,0.004689063,0.0002503876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09043542,0.00003806697,0.9070275,0.0003372975,0.0001567147,0.0008190742,0.00001684722,0.000304097,0.0008649497],"genre_scores_gemma":[0.9712367,0.000004651559,0.02809763,0.0003741776,0.00003430256,0.0001740747,0.00004801863,0.0000154744,0.00001497502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8808013,"threshold_uncertainty_score":0.4672122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05980128379169978,"score_gpt":0.267698934900163,"score_spread":0.2078976511084632,"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."}}