{"id":"W4244486989","doi":"10.22201/fi.25940732e.2008.09n2.013","title":"Artificial learning approaches for the nextgeneration web: Part II","year":2008,"lang":"es","type":"article","venue":"Ingeniería Investigación y Tecnología","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centrale des Syndicats du Québec","funders":"Division of Mathematical Sciences; University of Nottingham; Instituto Tecnológico y de Estudios Superiores de Monterrey; Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California; Griffith University; Universidad de Colima","keywords":"Ontology; Semantic Web; Computer science; Relation (database); Point (geometry); Ontology learning; OWL-S; Process (computing); Domain (mathematical analysis); Semantic Web Stack; Social Semantic Web; Information retrieval; Ontology Inference Layer; Upper ontology; Artificial intelligence; World Wide Web; Data mining; Suggested Upper Merged Ontology; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001035791,0.0005564917,0.0005460295,0.0002439064,0.003997917,0.0004896878,0.001712375,0.0005130352,0.00002496875],"category_scores_gemma":[0.001693188,0.0004204921,0.0003130486,0.0007336159,0.0015928,0.0006055025,0.0007076651,0.0007635163,0.0001065033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008658395,"about_ca_system_score_gemma":0.0006124637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007562291,"about_ca_topic_score_gemma":0.00006588372,"domain_scores_codex":[0.9962175,0.0003068427,0.0008398929,0.001086745,0.0005152262,0.001033729],"domain_scores_gemma":[0.9973026,0.0007739516,0.0004531371,0.001093578,0.0001896809,0.0001870701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001783307,0.0006368352,0.03717178,0.0002641086,0.0007342253,0.0001303716,0.0159045,0.02474651,0.01379174,0.475833,0.04995573,0.3806529],"study_design_scores_gemma":[0.0006499381,0.001074815,0.006213719,0.00009900687,0.000236406,0.0001878369,0.0007085502,0.6597867,0.03475515,0.01777861,0.2773123,0.001196928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8583177,0.00936373,0.0949958,0.02878038,0.004343222,0.001618149,0.00002064,0.001120005,0.001440407],"genre_scores_gemma":[0.979645,0.0006181245,0.01507927,0.001118345,0.001768733,0.000332083,0.00001991191,0.00005076083,0.001367781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6350402,"threshold_uncertainty_score":0.9998247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1596590585484493,"score_gpt":0.2650919862814279,"score_spread":0.1054329277329787,"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."}}