{"id":"W3201840680","doi":"10.1109/icas49788.2021.9551114","title":"Matching Models for Crowd-Shipping Considering Shipper’s Acceptance Uncertainty","year":2021,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Flexibility (engineering); Computer science; Compensation (psychology); Operations research; Engineering; Economics","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":[0.00008895342,0.0001039733,0.0001237134,0.00004157256,0.0000897571,0.00005530258,0.00006043545,0.00005162914,0.0002173235],"category_scores_gemma":[0.00001797577,0.0001176555,0.00006210413,0.0001847523,0.00001439183,0.0002447521,0.000005969712,0.00009631466,0.000005802495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000497584,"about_ca_system_score_gemma":0.00004765268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001886287,"about_ca_topic_score_gemma":0.0008229302,"domain_scores_codex":[0.9993102,0.000005264676,0.0002499891,0.0001575843,0.0000767849,0.0002001852],"domain_scores_gemma":[0.9995512,0.0000840908,0.00001405665,0.000171823,0.0001352862,0.00004352753],"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":[0.000002003797,0.000009277449,0.00005295614,0.00009140698,0.00003043741,0.000002248034,0.0007722913,0.8283499,0.009910809,0.1585149,0.0003085241,0.001955221],"study_design_scores_gemma":[0.001345629,0.00001315883,0.001496673,0.0001411886,0.0000524523,0.00001799216,0.006488465,0.8023995,0.04107565,0.1265749,0.01952837,0.0008659748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1795149,0.000112554,0.8093124,0.000477783,0.0002865586,0.0001711176,0.00002859094,0.0005617794,0.009534287],"genre_scores_gemma":[0.9678466,0.00001725242,0.03113837,0.0004714016,0.00003703053,0.00006443664,0.00005565177,0.000023868,0.0003453814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7883317,"threshold_uncertainty_score":0.4797853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04016002141142644,"score_gpt":0.2641059082719683,"score_spread":0.2239458868605418,"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."}}