{"id":"W2050483123","doi":"10.1145/1774088.1774383","title":"Evidential reasoning for the treatment of incoherent terminologies","year":2010,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; National Research Council Canada","funders":"","keywords":"Axiom; Correctness; Computer science; Ontology; Perspective (graphical); Focus (optics); Set (abstract data type); Ranking (information retrieval); Artificial intelligence; Description logic; Information retrieval; Epistemology; Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01836325,0.001095116,0.00158341,0.003784663,0.002696057,0.00394176,0.003645729,0.003551819,0.003454173],"category_scores_gemma":[0.03263539,0.0009948247,0.002545264,0.003455608,0.009639336,0.009392926,0.005435714,0.007724978,0.0006034186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002966409,"about_ca_system_score_gemma":0.002346251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089483,"about_ca_topic_score_gemma":0.001546687,"domain_scores_codex":[0.9879591,0.006156319,0.001028426,0.0007891734,0.003748675,0.0003182996],"domain_scores_gemma":[0.9779969,0.01696441,0.001028512,0.002253365,0.001492498,0.0002642591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009065806,0.00001238642,0.00006456972,0.0001137728,0.00002577362,0.0001453447,0.0003961221,0.008209446,0.000278219,0.9815072,0.0007387862,0.00849943],"study_design_scores_gemma":[0.000008942027,0.000005539368,0.00001574647,0.00003370283,0.00001074103,0.00003826643,0.00002872259,0.02813817,0.0002077239,0.9687787,0.00272597,0.000007900378],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002559424,0.001472214,0.9889262,0.001525006,0.0001295429,0.0000583591,0.00004107505,0.00009566679,0.00519247],"genre_scores_gemma":[0.1468618,0.001971861,0.8458543,0.0007925777,0.0006150443,0.0003910438,0.0002121486,0.00009408159,0.003207151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01836325,"threshold_uncertainty_score":0.09711534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03521563671066608,"score_gpt":0.3021076742837315,"score_spread":0.2668920375730655,"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."}}