{"id":"W4408696798","doi":"10.1109/itsc58415.2024.10919661","title":"Modelling Link-Level Shared Micromobility Demand: Regression and Neural Network Approaches","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial neural network; Computer network; Link (geometry); Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002545853,0.001219361,0.0007857633,0.001434823,0.0003593286,0.001264029,0.001516928,0.001299388,0.002686103],"category_scores_gemma":[0.008451067,0.0005957002,0.0008968795,0.00175501,0.0003974498,0.001824754,0.001044614,0.001603767,0.0004564592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387815,"about_ca_system_score_gemma":0.0008695041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0588902,"about_ca_topic_score_gemma":0.03342934,"domain_scores_codex":[0.9990718,0.0004789639,0.00004570033,0.0001936533,0.00009028572,0.0001195126],"domain_scores_gemma":[0.9957018,0.003463444,0.0003277289,0.00009076521,0.0003372951,0.00007889308],"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":[0.0001053808,0.0001942724,0.01953628,0.00004493494,0.0001664269,0.00007933339,0.00007489982,0.9528729,0.0001985836,0.002216243,0.0004965658,0.02401423],"study_design_scores_gemma":[0.000002054887,0.00001131075,0.0008810996,0.000003406734,0.000006058895,0.000002950305,0.00002202976,0.9983607,0.00002623149,0.0006259682,0.00005451856,0.000003764576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6057435,0.001131877,0.3841909,0.001577994,0.0001193713,0.0001768874,0.001306781,0.0005719271,0.005180744],"genre_scores_gemma":[0.9583652,0.0004567308,0.03672473,0.00007558738,0.0000663521,0.0001472184,0.0008259846,0.0000406086,0.003297574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0588902,"threshold_uncertainty_score":0.1170948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08756493789090866,"score_gpt":0.2441077113421913,"score_spread":0.1565427734512826,"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."}}