{"id":"W2170431068","doi":"10.1613/jair.4031","title":"Horn Clause Contraction Functions","year":2013,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Horn clause; Contraction (grammar); Propositional calculus; French horn; Remainder; Mathematics; Classical logic; Forgetting; Computer science; Algorithm; Discrete mathematics; Artificial intelligence; Logic programming; Arithmetic; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002728389,0.0001102728,0.0002057331,0.0005364262,0.0003860327,0.000676234,0.001014576,0.0001080926,0.0004895901],"category_scores_gemma":[0.001104297,0.0000842592,0.0001494237,0.000994377,0.0001875679,0.00144318,0.0001592922,0.0009493046,0.002688553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575005,"about_ca_system_score_gemma":0.0003316185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001705551,"about_ca_topic_score_gemma":0.00005440811,"domain_scores_codex":[0.9973788,0.0003392847,0.0006271602,0.000225518,0.0009033949,0.0005258832],"domain_scores_gemma":[0.9959939,0.0006664134,0.0002156966,0.000360756,0.002462233,0.0003009653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005589201,0.0005592451,0.000412866,0.00001366874,0.00006066765,0.00006732231,0.001588644,0.000279678,0.02286786,0.1183729,0.02188731,0.833834],"study_design_scores_gemma":[0.0002429305,0.004099753,0.005876591,0.0002244597,0.00003648499,0.0008385291,0.008411556,0.1503674,0.1582769,0.6061084,0.0646884,0.0008286556],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07860643,0.0004680957,0.9058334,0.004013521,0.001863279,0.0002796868,5.809555e-7,0.0000475538,0.008887419],"genre_scores_gemma":[0.9943209,0.0001735735,0.003470995,0.00004207826,0.0008354946,0.00001095524,2.712225e-7,0.000008563592,0.001137203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9157144,"threshold_uncertainty_score":0.9980879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1545227878795776,"score_gpt":0.3942431817833369,"score_spread":0.2397203939037593,"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."}}