{"id":"W2262233962","doi":"","title":"Yet Another Matcher","year":2009,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Schema matching; Computer science; Schema (genetic algorithms); Matching (statistics); Precision and recall; Artificial intelligence; Data mining; Machine learning; Data integration; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01159224,0.001650869,0.00197946,0.003917269,0.001652931,0.004887469,0.003120849,0.003608801,0.0207513],"category_scores_gemma":[0.02629084,0.00138175,0.003103117,0.003346805,0.001322408,0.009407198,0.005978799,0.002505488,0.01133547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069883,"about_ca_system_score_gemma":0.001529134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000834597,"about_ca_topic_score_gemma":0.000644397,"domain_scores_codex":[0.9889043,0.002026142,0.001602569,0.004112828,0.002808735,0.0005454904],"domain_scores_gemma":[0.9851547,0.004306589,0.0007895853,0.007481406,0.001879306,0.0003885217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001255109,0.000466707,0.009416491,0.001333789,0.000866694,0.0009022729,0.001722606,0.0080014,0.04619825,0.08885244,0.06017357,0.7808107],"study_design_scores_gemma":[0.0002818391,0.0006869633,0.004454129,0.0004256491,0.0007707834,0.003876169,0.001222194,0.1427535,0.1620486,0.1258675,0.5573201,0.0002926557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01202251,0.0006086891,0.9480355,0.0008519589,0.0003918589,0.0004468448,0.001595147,0.02845687,0.007590527],"genre_scores_gemma":[0.07612984,0.0003470461,0.904781,0.001254505,0.0001182048,0.0003081383,0.00390815,0.004114639,0.009038409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0207513,"threshold_uncertainty_score":0.06941998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349139047445786,"score_gpt":0.2217862934674317,"score_spread":0.2082949029929738,"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."}}