{"id":"W2371354481","doi":"","title":"Optimizing Method for Ontology Mapping Based on Similarity Computation","year":2008,"lang":"en","type":"article","venue":"Jisuanji gongcheng","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Ontology; Computation; Similarity (geometry); Data mining; Information retrieval; Theoretical computer science; Algorithm; Artificial intelligence; Image (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":[0.001131273,0.0004875701,0.0009058879,0.001118771,0.0009214003,0.0009764717,0.001137802,0.0005976172,0.003238479],"category_scores_gemma":[0.003141668,0.0002666255,0.0006869422,0.00111455,0.000479539,0.002270215,0.0008998604,0.0005427664,0.0004140042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102152,"about_ca_system_score_gemma":0.001740448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005136623,"about_ca_topic_score_gemma":0.004453601,"domain_scores_codex":[0.9989331,0.0002808473,0.00006554474,0.0002462605,0.0003978348,0.00007640911],"domain_scores_gemma":[0.9992805,0.000279266,0.00005396196,0.0001260346,0.0002297219,0.00003055036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001843243,0.00021583,0.00210274,0.0002338105,0.0001272783,0.0001200823,0.0003461613,0.1099157,0.01291372,0.1019916,0.006736922,0.7651119],"study_design_scores_gemma":[0.00004637471,0.00004915502,0.0007060848,0.000007505678,0.00004083482,0.00009277265,0.0000683017,0.9572508,0.004687302,0.03444345,0.002588162,0.0000192008],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01522993,0.00009979167,0.982026,0.0001210332,0.00003196818,0.00006238452,0.0000212973,0.0003728788,0.002034651],"genre_scores_gemma":[0.3075096,0.0001523879,0.6883474,0.00006451075,0.00003048216,0.0001846915,0.0001545414,0.0001336636,0.003422825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005136623,"threshold_uncertainty_score":0.01083374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07780568782515306,"score_gpt":0.3661050605442266,"score_spread":0.2882993727190735,"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."}}