{"id":"W4404832725","doi":"10.2139/ssrn.5037025","title":"Dynamic Bike Repositioning Optimization Based on Full Coupling Analysis and Reinforcement Learning with Heuristics","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Elevator Systems and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Reinforcement learning; Heuristics; Computer science; Coupling (piping); Reinforcement; Artificial intelligence; Engineering; Structural engineering; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001130402,0.001365418,0.002580238,0.0009517401,0.0006467082,0.001208757,0.001394979,0.001702179,0.004111235],"category_scores_gemma":[0.003337226,0.001085182,0.000762039,0.0007061737,0.001186851,0.001535384,0.001611444,0.00159413,0.0004172631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418449,"about_ca_system_score_gemma":0.001641158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01029946,"about_ca_topic_score_gemma":0.006315313,"domain_scores_codex":[0.9995634,0.0001436173,0.00002024301,0.00009475757,0.0000740421,0.0001040145],"domain_scores_gemma":[0.9982187,0.001259995,0.0001585268,0.00008881032,0.0001486686,0.0001253397],"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":[0.00004145373,0.00002415002,0.0000937987,0.00002009916,0.00001570724,0.00001218616,0.00001164043,0.993162,0.0002109364,0.001569079,0.0001982627,0.004640606],"study_design_scores_gemma":[0.000007298868,0.00001315283,0.0000263525,0.000002467498,0.000003433069,0.000002309828,0.00000214466,0.9991202,0.0000357576,0.0007502871,0.00003439572,0.000002267339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05896966,0.0003970621,0.9320521,0.0002356598,0.00007974992,0.00007824942,0.0000598941,0.0004312746,0.007696334],"genre_scores_gemma":[0.9472249,0.0001097142,0.04878156,0.00009319632,0.00003510214,0.0001402414,0.00007066855,0.0001071174,0.003437446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01029946,"threshold_uncertainty_score":0.02047902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002222282907831646,"score_gpt":0.1894513578713224,"score_spread":0.1872290749634907,"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."}}