{"id":"W2241491522","doi":"10.1109/ictai.2015.88","title":"On the Assessment of Concept Relevance in FCA-Based Ontology Restructuring","year":2015,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Ontology; Computer science; Relevance (law); Restructuring; Context (archaeology); Process (computing); Set (abstract data type); Quality (philosophy); Formal concept analysis; Information retrieval; Process ontology; Data mining; Semantic Web; Algorithm; Programming language","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":[0.01791542,0.0009928175,0.001696701,0.009899643,0.002347598,0.003599445,0.002569853,0.00230842,0.001286288],"category_scores_gemma":[0.08045351,0.0004501563,0.00116039,0.004575147,0.002416302,0.00358971,0.002291788,0.001862151,0.0005420173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002617537,"about_ca_system_score_gemma":0.002942084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01446199,"about_ca_topic_score_gemma":0.01379284,"domain_scores_codex":[0.9850174,0.004839642,0.001109428,0.001893388,0.006596121,0.0005440601],"domain_scores_gemma":[0.9465862,0.03812821,0.002974011,0.003723123,0.007691669,0.0008968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007469087,0.0006720413,0.02250657,0.000457759,0.000278553,0.0006063717,0.002282685,0.1090475,0.02016333,0.02927738,0.003594265,0.8103665],"study_design_scores_gemma":[0.00004248232,0.0001854741,0.009001329,0.0001322424,0.0001425001,0.0004115335,0.0004039206,0.9365326,0.01862869,0.03115594,0.003284141,0.00007912792],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1054578,0.001085441,0.8852946,0.00050869,0.00005779689,0.0006488721,0.0001872028,0.001523701,0.005235902],"genre_scores_gemma":[0.4710565,0.0002249134,0.5268276,0.0001495816,0.0000474686,0.0002258391,0.0003550765,0.0001525165,0.0009605951],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01791542,"threshold_uncertainty_score":0.09474695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05512943753898645,"score_gpt":0.3117424071013756,"score_spread":0.2566129695623892,"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."}}