{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0124075,0.001912844,0.002156748,0.003339782,0.002230961,0.00598109,0.00755791,0.003482656,0.01409776],"category_scores_gemma":[0.0795828,0.001945086,0.003472291,0.007731981,0.007372735,0.02039525,0.007809623,0.01006228,0.001776946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003969122,"about_ca_system_score_gemma":0.004286303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009148496,"about_ca_topic_score_gemma":0.007374829,"domain_scores_codex":[0.9841713,0.006451881,0.0008231323,0.003724563,0.004221656,0.0006075026],"domain_scores_gemma":[0.928386,0.05336497,0.002617556,0.01056573,0.004204459,0.0008613989],"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":[0.00008956179,0.00008500819,0.001417363,0.0005404158,0.0001973987,0.000113592,0.0003497982,0.08787839,0.0008925786,0.7545962,0.008351231,0.1454884],"study_design_scores_gemma":[0.00001833995,0.00001398008,0.0002114617,0.00005645956,0.00003163511,0.0001179264,0.00004440979,0.2005905,0.001032741,0.7926286,0.005221168,0.0000327616],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00167911,0.0002816177,0.9945933,0.0007086378,0.00004330122,0.00004155875,0.0001349461,0.0002336294,0.002283912],"genre_scores_gemma":[0.1150795,0.0007903639,0.8794323,0.0006274313,0.0002719701,0.0002120868,0.0006243561,0.0005057883,0.002456256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01409776,"threshold_uncertainty_score":0.06561792,"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."}}