{"id":"W1865476398","doi":"","title":"Towards unbiased evaluation of uncertainty reasoning: The URREF ontology","year":2012,"lang":"en","type":"article","venue":"International Conference on Information Fusion","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Ontology; Computer science; Situation awareness; Sensor fusion; Representation (politics); Situation analysis; Knowledge representation and reasoning; Data mining; Ontology-based data integration; Data collection; Information retrieval; Data science; Artificial intelligence; Engineering; Semantic Web","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":[0.001436224,0.0001027667,0.0001084972,0.0001560174,0.00009370995,0.00009537383,0.0007945606,0.00007015069,0.0002810501],"category_scores_gemma":[0.0006197824,0.0000684543,0.00005170409,0.000152569,0.00006156231,0.001431885,0.0001508686,0.0001135904,0.0001103595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001040028,"about_ca_system_score_gemma":0.0001938907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002031454,"about_ca_topic_score_gemma":0.00002579447,"domain_scores_codex":[0.9982794,0.0001410335,0.0003647316,0.00009332295,0.0009534931,0.0001679975],"domain_scores_gemma":[0.99825,0.00009856189,0.0003233129,0.0003150281,0.0009702747,0.00004283766],"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":[0.00002745296,0.00004231485,0.001037218,0.000004094209,0.00001646435,8.318506e-8,0.002627523,0.0006011918,0.0001336487,0.851454,0.0007258325,0.1433302],"study_design_scores_gemma":[0.001151249,0.0001412684,0.1144678,0.00009347755,0.00002517196,0.00002176914,0.001507764,0.8512344,0.002885639,0.01449847,0.01374261,0.0002303734],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4637481,0.00009263247,0.1688111,0.01322048,0.005344749,0.0006864214,0.00002029739,0.0001967899,0.3478794],"genre_scores_gemma":[0.9980421,0.00002108799,0.001226125,0.0005480183,0.00006007775,0.00002896785,0.00003934294,0.000001612798,0.00003266224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8506332,"threshold_uncertainty_score":0.3077301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08811752557596993,"score_gpt":0.3427408974872192,"score_spread":0.2546233719112493,"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."}}