{"id":"W4413156244","doi":"10.1109/cvpr52734.2025.02522","title":"MATCHA: Towards Matching Anything","year":2025,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","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":[0.0002436386,0.00006009734,0.00008395901,0.00009515847,0.00009177469,0.0002528835,0.0005850587,0.00003037359,0.00002534845],"category_scores_gemma":[0.00001153236,0.00005185411,0.00003677386,0.0002869401,0.000008394391,0.0002811928,0.0001940038,0.00006334309,0.0001375228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002100225,"about_ca_system_score_gemma":0.00004795576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001385711,"about_ca_topic_score_gemma":0.00001375455,"domain_scores_codex":[0.9993649,0.0000323363,0.0001543314,0.0001884108,0.0001302394,0.0001297515],"domain_scores_gemma":[0.9994949,0.00002431094,0.00002378404,0.0003863139,0.00003592329,0.00003482799],"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":[3.658577e-7,0.00002030699,0.0001423384,0.00002332207,0.00001067115,0.000001918894,0.01920005,0.000001204445,0.0003608134,0.9640962,0.002260763,0.01388206],"study_design_scores_gemma":[0.0007935443,0.00002822585,0.01078476,0.0002041524,0.00001383538,0.00002710461,0.001756667,0.3982445,0.008327518,0.4458812,0.1333363,0.0006021841],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0190522,0.00006058117,0.9019721,0.007647098,0.0006399766,0.00008140448,2.072456e-7,0.000369296,0.07017719],"genre_scores_gemma":[0.9802007,0.000002532727,0.008533057,0.001891288,0.00001631553,0.000005831809,3.919081e-7,0.000002126191,0.00934775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9611485,"threshold_uncertainty_score":0.2438562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216168595823875,"score_gpt":0.2666514030868782,"score_spread":0.2544897171286394,"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."}}