{"id":"W207039527","doi":"","title":"Fuzziness in the Semantic Web: Survey and Future Directions.","year":2008,"lang":"en","type":"article","venue":"Software Engineering and Knowledge Engineering","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Semantic Web; Social Semantic Web; World Wide Web; Information retrieval; Data science","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":[0.0004211442,0.0002141156,0.00022298,0.0002146473,0.0001169009,0.00007692962,0.0003275219,0.00008740576,7.579086e-7],"category_scores_gemma":[0.0003019367,0.0001692958,0.00003139646,0.0006291398,0.00002664789,0.0002186689,0.0001231096,0.0002609596,0.000003917969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001931959,"about_ca_system_score_gemma":0.00003134254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003323554,"about_ca_topic_score_gemma":0.00005036865,"domain_scores_codex":[0.9990683,0.00003740015,0.0001789889,0.0002976228,0.00010658,0.000311123],"domain_scores_gemma":[0.9990306,0.0005573895,0.000018972,0.0002919406,0.00003651473,0.0000646031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003021956,0.0005270073,0.7060125,0.002470353,0.0003159989,0.000948558,0.0580928,0.02079406,0.001154867,0.02794578,0.002736926,0.1789709],"study_design_scores_gemma":[0.0003596293,0.00003123086,0.789054,0.00007378976,0.00000590815,0.00045831,0.00006789545,0.1860587,0.00004635111,0.00001367176,0.02343457,0.00039595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8539929,0.02016775,0.1228391,0.0002004696,0.001656772,0.0001831706,0.00000316213,0.000890357,0.00006635964],"genre_scores_gemma":[0.988115,0.001449457,0.01008721,0.00001522372,0.0002485463,0.00002604064,0.000002188119,0.00001939163,0.00003695803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.178575,"threshold_uncertainty_score":0.6903684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01350267997103201,"score_gpt":0.2120377637081326,"score_spread":0.1985350837371005,"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."}}