{"id":"W3140464205","doi":"","title":"Investigating the characteristics of one-sided matching mechanisms","year":2016,"lang":"en","type":"article","venue":"Adaptive Agents and Multi-Agents Systems","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Matching (statistics); Mathematics; 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":[0.00147705,0.0002241982,0.0005711057,0.0001051415,0.0002247112,0.0000722484,0.0002870093,0.000106602,0.00005124188],"category_scores_gemma":[0.0002554304,0.0001534818,0.00009446022,0.0001121409,0.0001292619,0.0001907092,0.0001275177,0.0001080523,0.0001471724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005064976,"about_ca_system_score_gemma":0.00001201531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007529811,"about_ca_topic_score_gemma":0.000008852188,"domain_scores_codex":[0.9980531,0.0001416478,0.0009745806,0.0004109503,0.00008945834,0.0003302268],"domain_scores_gemma":[0.9981791,0.0002346313,0.001032863,0.0003734209,0.00006317602,0.0001167761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002671132,0.0001876579,0.04949922,0.0002448343,0.0004862732,0.000006022313,0.005706892,0.00002636484,0.006874439,0.9345158,0.0001787069,0.002247079],"study_design_scores_gemma":[0.01145249,0.0009879706,0.7851835,0.007694835,0.0002584202,0.00009854651,0.01234464,0.0354766,0.003321418,0.1251157,0.0146992,0.003366686],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9276592,0.0005293878,0.06752864,0.0001615532,0.001293575,0.0007542121,0.0003777164,0.00004951013,0.001646213],"genre_scores_gemma":[0.99664,0.00007849398,0.0006263236,0.0001136623,0.0001123222,0.00004347465,0.000005192,0.00003683872,0.002343723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8094001,"threshold_uncertainty_score":0.6258805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1092659491931415,"score_gpt":0.2541527099557087,"score_spread":0.1448867607625672,"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."}}