{"id":"W2621605989","doi":"10.1109/tits.2017.2704418","title":"A Bargaining-Based Solution to the Team Mobility Planning Game","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Game theory; Computer science; Mathematical economics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001157648,0.000798211,0.0007179018,0.0005288457,0.0009360651,0.001201761,0.001880047,0.001662782,0.006128155],"category_scores_gemma":[0.001936147,0.0003804133,0.0009117168,0.0006687272,0.0009041413,0.001048803,0.001990789,0.001300613,0.000703373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009472147,"about_ca_system_score_gemma":0.001890233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002300231,"about_ca_topic_score_gemma":0.001918607,"domain_scores_codex":[0.999325,0.0002894713,0.00002754656,0.0001169714,0.0001408847,0.0001000759],"domain_scores_gemma":[0.9996293,0.0001994241,0.0000411156,0.00001928956,0.00006111817,0.00004972355],"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":[0.00005586208,0.0000442967,0.0001746943,0.0001008249,0.00002957096,0.0002056566,0.0002345697,0.7427308,0.001721259,0.2322617,0.001955174,0.02048556],"study_design_scores_gemma":[0.0000254145,0.00006002955,0.00004975319,0.00001835889,0.00001115527,0.00006085961,0.0000836609,0.9497852,0.0003774152,0.0459282,0.003587866,0.00001204482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005954347,0.00006533782,0.9813517,0.0002077664,0.00004188106,0.00008837644,0.00004248346,0.00004212207,0.01220599],"genre_scores_gemma":[0.4790526,0.0003555459,0.5052412,0.0001409834,0.0000575215,0.0006066522,0.0001526326,0.00006454949,0.01432837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006128155,"threshold_uncertainty_score":0.02050072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04292315226687154,"score_gpt":0.2846960413595115,"score_spread":0.24177288909264,"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."}}