{"id":"W2100078804","doi":"10.1093/logcom/exi021","title":"Expressing Default Logic Variants in Default Logic","year":2005,"lang":"en","type":"article","venue":"Journal of Logic and Computation","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Default logic; Non-monotonic logic; Default rule; Unification; Extension (predicate logic); Computer science; Interpretation (philosophy); Autoepistemic logic; Artificial intelligence; Many-valued logic; Multimodal logic; Mathematics; Theoretical computer science; Description logic; 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":[],"consensus_categories":[],"category_scores_codex":[0.0007334146,0.0001721628,0.000319776,0.0002345679,0.0001332868,0.0002151694,0.0004051273,0.0001191229,0.00001138097],"category_scores_gemma":[0.0001298323,0.000127574,0.00008531383,0.0003210913,0.00005212641,0.0008083858,0.0001237269,0.0002864034,0.00002121437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008901181,"about_ca_system_score_gemma":0.00008875285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008825719,"about_ca_topic_score_gemma":0.00001017365,"domain_scores_codex":[0.9984226,0.0001818927,0.0005682413,0.0002533758,0.0002919477,0.0002820086],"domain_scores_gemma":[0.998848,0.0001928862,0.0004906654,0.0001242347,0.0002221297,0.0001220933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000142623,0.001096774,0.00932544,0.00009083761,0.0000804746,0.000742272,0.00831145,0.1040419,0.003298426,0.1616406,0.003007176,0.708222],"study_design_scores_gemma":[0.003182797,0.0009112873,0.08742914,0.0002539779,0.00003671096,0.001595802,0.0004050226,0.53619,0.0002877972,0.36784,0.001296049,0.0005714563],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1050821,0.002076207,0.8862758,0.001172972,0.0003709493,0.00009147116,3.577063e-7,0.00004007095,0.004890058],"genre_scores_gemma":[0.9132041,0.0001036811,0.0857093,0.0006413755,0.0002771569,0.000001407213,9.138197e-7,0.00000549674,0.00005651061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.808122,"threshold_uncertainty_score":0.5202318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03056074398423831,"score_gpt":0.2893305849371426,"score_spread":0.2587698409529043,"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."}}