{"id":"W3187284326","doi":"10.24963/ijcai.2021/45","title":"Improving Welfare in One-Sided Matchings using Simple Threshold Queries","year":2021,"lang":"en","type":"article","venue":"","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Matching (statistics); Property (philosophy); Simple (philosophy); Object (grammar); Preference; Mathematical optimization; Computer science; Pareto principle; Rank (graph theory); Pareto optimal; Mathematics; Mathematical economics; Algorithm; Artificial intelligence; Multi-objective optimization; Combinatorics; Statistics","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":[0.0006294161,0.0001222317,0.00036247,0.0001283917,0.0001179823,0.0001214498,0.0001252448,0.0000881873,0.000757186],"category_scores_gemma":[0.0001901057,0.000149767,0.00007717845,0.0002428905,0.00002497163,0.0002685168,0.00006989367,0.0001473945,0.00008122341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008172396,"about_ca_system_score_gemma":0.00001953631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00187837,"about_ca_topic_score_gemma":0.0003866078,"domain_scores_codex":[0.9987495,0.00002040204,0.0005598999,0.000353798,0.0000264334,0.0002899445],"domain_scores_gemma":[0.9994131,0.00004361562,0.0001874701,0.0002874311,0.00002205413,0.0000462956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007607144,0.00004898495,0.07619007,0.00007708988,0.000016986,0.00001771775,0.0006712296,0.0002326355,0.001244093,0.9211635,0.00001689127,0.0003132088],"study_design_scores_gemma":[0.003567448,0.0001281025,0.1012882,0.0004126194,0.00002626501,0.0001302407,0.01400511,0.06585664,0.02070457,0.7752339,0.01602401,0.002622944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615975,0.0005171976,0.002645416,0.0003475917,0.0002516648,0.00009385459,0.00002143087,0.00005816605,0.03446716],"genre_scores_gemma":[0.9973412,0.000005609181,0.001386583,0.0001688343,0.0000703353,0.000005405226,0.000007909674,0.00001923144,0.000994865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1459296,"threshold_uncertainty_score":0.8290656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06142487504616668,"score_gpt":0.2360297590930548,"score_spread":0.1746048840468881,"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."}}