{"id":"W2911930742","doi":"10.1613/jair.1.11337","title":"A Generalisation of AGM Contraction and Revision to Fragments of First-Order Logic","year":2019,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Griffith University","keywords":"Contraction (grammar); Logical equivalence; Propositional calculus; Horn clause; Classical logic; Mathematics; Non-monotonic logic; Many-valued logic; Intermediate logic; Equivalence (formal languages); Substructural logic; Expressive power; Description logic; Algorithm; Computer science; Discrete mathematics; Theoretical computer science; Prolog; Linguistics; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004510775,0.0005978172,0.0005001902,0.001380666,0.001022738,0.002152227,0.002126246,0.001315515,0.004075732],"category_scores_gemma":[0.01006046,0.0003941829,0.001742705,0.001173001,0.004587142,0.005795219,0.002925538,0.003372946,0.0005783805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002303611,"about_ca_system_score_gemma":0.001492714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923755,"about_ca_topic_score_gemma":0.001326667,"domain_scores_codex":[0.996849,0.0009399248,0.0001825188,0.000661356,0.001082845,0.0002843186],"domain_scores_gemma":[0.9953903,0.001748153,0.0003583074,0.001604485,0.0006933952,0.0002052706],"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":[0.00003370815,0.00002001593,0.0003099336,0.00004508078,0.00001532016,0.000115918,0.0007968029,0.004077212,0.001975151,0.9581212,0.0008225252,0.03366719],"study_design_scores_gemma":[0.00003693821,0.0001050759,0.0006400463,0.00004048984,0.00003040773,0.0004988713,0.0001895822,0.05360989,0.004086105,0.9172707,0.02344497,0.00004692771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03070925,0.0004532672,0.93535,0.001152464,0.0001032108,0.0001795631,0.0001494575,0.0004388326,0.03146397],"genre_scores_gemma":[0.6446765,0.0004222936,0.3398947,0.0006750866,0.0002844495,0.0002880545,0.0002120607,0.0001705196,0.01337645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004510775,"threshold_uncertainty_score":0.02385557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1294825634957763,"score_gpt":0.4023719552677477,"score_spread":0.2728893917719714,"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."}}