{"id":"W2530744162","doi":"10.1016/j.ijar.2016.10.001","title":"Negative probabilities in probabilistic logic programs","year":2016,"lang":"en","type":"article","venue":"International Journal of Approximate Reasoning","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Negation; Probabilistic logic; Inference; Computer science; Representation (politics); Propositional calculus; Translation (biology); Mathematics; Theoretical computer science; Algorithm; Artificial intelligence; Discrete mathematics; Programming language","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":[0.00697037,0.001044682,0.001309005,0.002190385,0.001895747,0.006160513,0.002498676,0.002500405,0.005256959],"category_scores_gemma":[0.03788928,0.001566605,0.001545109,0.002660427,0.006266261,0.01430921,0.003541462,0.005720539,0.0004557788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003277978,"about_ca_system_score_gemma":0.001563971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003673567,"about_ca_topic_score_gemma":0.004069821,"domain_scores_codex":[0.9936539,0.003004004,0.00037077,0.0007648207,0.001849633,0.0003569011],"domain_scores_gemma":[0.9587166,0.03667155,0.001582176,0.0009647603,0.00142706,0.0006378263],"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":[0.00004609623,0.00002712994,0.0003886233,0.00006544207,0.00001464371,0.0001006188,0.0002582222,0.009506423,0.0001620435,0.9834051,0.0005521222,0.005473617],"study_design_scores_gemma":[0.000008237585,0.000002979989,0.00003881525,0.000008820074,0.000007843457,0.00002252674,0.00001882985,0.0285512,0.00006578303,0.9708299,0.0004400255,0.00000490699],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05172625,0.0008497095,0.9288603,0.003776377,0.00009789278,0.0000480395,0.0002202751,0.0002863168,0.01413493],"genre_scores_gemma":[0.787308,0.001104946,0.1976576,0.0009141754,0.0004657408,0.0002439502,0.0005766751,0.0002330666,0.01149598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00697037,"threshold_uncertainty_score":0.03686333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028430107919862,"score_gpt":0.2779849560138782,"score_spread":0.2495548480940162,"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."}}