{"id":"W4408397987","doi":"10.1016/j.eswa.2025.127233","title":"Unbiased criteria identification for two-sided matching: An environment-based design approach","year":2025,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Identification (biology); Matching (statistics); Data mining; Artificial intelligence; Machine learning; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001221237,0.0002041544,0.0003825992,0.0002311198,0.0003673792,0.000220237,0.000363568,0.00009637203,0.00002012341],"category_scores_gemma":[0.0000270101,0.0002132625,0.00006958138,0.0002484115,0.00006583204,0.0001816143,0.0000143911,0.00007399715,0.0001210132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001329439,"about_ca_system_score_gemma":0.0000363643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002163795,"about_ca_topic_score_gemma":0.000002199585,"domain_scores_codex":[0.9981738,0.00009909305,0.0007584233,0.0006604043,0.00004765678,0.0002606193],"domain_scores_gemma":[0.9983395,0.000196948,0.0004408575,0.000895437,0.0000419269,0.00008533995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001117655,0.0005222847,0.0004292894,0.0002432328,0.0001050057,2.229192e-7,0.001012084,0.02007851,0.006640346,0.9691696,0.00140652,0.0002811012],"study_design_scores_gemma":[0.009169982,0.0004626353,0.001770535,0.0004528334,0.0001139163,0.00002129597,0.00641221,0.6976165,0.01025387,0.07325838,0.1979706,0.002497306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002502146,0.0007273603,0.9906139,0.0001732037,0.0001768906,0.003089284,0.0001219604,0.0001481323,0.002447145],"genre_scores_gemma":[0.9644774,0.000003213094,0.02144712,0.0001374739,0.0001612645,0.01165122,0.0002637401,0.00004199446,0.001816637],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9691668,"threshold_uncertainty_score":0.8696592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05475716662173801,"score_gpt":0.2818182935625275,"score_spread":0.2270611269407895,"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."}}