{"id":"W3037647357","doi":"10.48550/arxiv.1604.05771","title":"Multidimensional matching","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; University of Alberta; National Science Foundation","keywords":"Matching (statistics); Context (archaeology); Economics; Monopoly; Microeconomics; Econometrics; Mathematical economics; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004331233,0.001219896,0.002090689,0.002174797,0.002091359,0.004263574,0.003231742,0.004437069,0.02506769],"category_scores_gemma":[0.01842977,0.0008184119,0.002447394,0.003479512,0.002761767,0.007481127,0.005072583,0.003524053,0.002701654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002821295,"about_ca_system_score_gemma":0.001146161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008816342,"about_ca_topic_score_gemma":0.0005154379,"domain_scores_codex":[0.9951885,0.002144315,0.0003023915,0.000964158,0.0008450238,0.0005556419],"domain_scores_gemma":[0.9923882,0.003283318,0.001358625,0.001693237,0.0006790284,0.000597537],"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":[0.00001200469,0.00003500351,0.0002458849,0.00005971579,0.0000275433,0.00005515055,0.00007085018,0.01484174,0.0001807136,0.9757448,0.001268505,0.007458078],"study_design_scores_gemma":[0.00001427137,0.00002715062,0.0001732851,0.00002920015,0.00001019279,0.00009801344,0.00004603397,0.07994568,0.0001387032,0.9146408,0.004862802,0.0000138337],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02098293,0.0009972461,0.9385647,0.001834637,0.0001551011,0.0001969423,0.000324242,0.00009907281,0.03684513],"genre_scores_gemma":[0.6830865,0.002716694,0.2610363,0.001422098,0.000738096,0.0009209853,0.0007371699,0.0001691692,0.049173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02506769,"threshold_uncertainty_score":0.08385974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09598282321915978,"score_gpt":0.172917010683524,"score_spread":0.07693418746436421,"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."}}