{"id":"W2125861280","doi":"10.48550/arxiv.1301.3864","title":"Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning","year":2013,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Probabilistic logic; Local consistency; Constraint (computer-aided design); Generalization; Consistency (knowledge bases); Reasoning system; Connection (principal bundle); Computer science; Theoretical computer science; Artificial intelligence; Mathematics; Mathematical optimization; Constraint satisfaction","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":[0.0002321912,0.0001865564,0.0002137264,0.0001587965,0.000313019,0.000200544,0.0002444732,0.00009875283,0.0001074309],"category_scores_gemma":[0.0003342306,0.000206771,0.00005746516,0.0005281092,0.000316914,0.0007950905,0.0001450306,0.0001866849,0.00005641178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001386428,"about_ca_system_score_gemma":0.0001411832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001812353,"about_ca_topic_score_gemma":0.00005138335,"domain_scores_codex":[0.9986345,0.0001344199,0.0002108163,0.0006476014,0.00007804737,0.0002945999],"domain_scores_gemma":[0.9987771,0.0002636654,0.0001564387,0.0003710335,0.0002189513,0.0002128276],"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":[0.000007658005,0.00003735426,0.0423195,0.0000475987,0.00005296453,0.00003385681,0.0003843855,0.01743269,0.00009844116,0.9262284,0.00007241911,0.0132847],"study_design_scores_gemma":[0.0008558438,0.0001187069,0.07049356,0.0001192037,0.00006560932,0.00007958651,0.0004128101,0.8844393,0.00004380183,0.04281111,0.0001033256,0.0004570979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4972951,0.00001430461,0.4978611,0.0002271306,0.0001119745,0.0004878894,0.000003333596,0.0002904851,0.003708663],"genre_scores_gemma":[0.9939307,0.00001479597,0.005719822,0.00006416153,0.00002808803,0.000003416093,0.000006011615,0.000009213478,0.0002238044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8834173,"threshold_uncertainty_score":0.8431876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614158244470897,"score_gpt":0.1783213174494765,"score_spread":0.1421797350047675,"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."}}