{"id":"W2148375944","doi":"10.1109/cwit.2007.375705","title":"On the Interpretation of Survey Propagation","year":2007,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Belief propagation; Probabilistic logic; Computer science; Constraint (computer-aided design); Decoupling (probability); Token passing; Security token; Message passing; Local consistency; Interpretation (philosophy); Reduction (mathematics); Propagation of uncertainty; Constraint satisfaction problem; Constraint satisfaction; Theoretical computer science; Artificial intelligence; Algorithm; Mathematics; Distributed computing; Computer security; Engineering; Programming language","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":[0.000764818,0.00002737664,0.00002784978,0.00004594853,0.00002798389,0.00001939279,0.0001075287,0.00001357904,0.00005615246],"category_scores_gemma":[0.0001545155,0.00001708716,0.00001245647,0.0001970353,0.00001672515,0.0001141497,0.00001363897,0.00002890041,0.00001473551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001095384,"about_ca_system_score_gemma":0.00001417939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003171595,"about_ca_topic_score_gemma":0.0001728182,"domain_scores_codex":[0.9996256,0.00004710598,0.0001103377,0.00006739204,0.0001053438,0.00004427195],"domain_scores_gemma":[0.9994097,0.0003190752,0.00005191351,0.0001270668,0.00008092911,0.00001133658],"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":[0.00001815717,0.00002335473,0.004699685,0.000002136083,0.000004906643,2.083667e-7,0.0004919393,0.002205311,0.0004071731,0.7414446,0.0004990321,0.2502035],"study_design_scores_gemma":[0.0001025575,0.00006044549,0.386167,0.000008797097,8.756735e-7,0.000001473726,0.00003515794,0.6003753,0.01024243,0.002917797,0.0000310132,0.00005720236],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01778933,8.136115e-7,0.9688079,0.0003517148,0.0001001653,0.00007916259,2.62803e-7,0.00003101331,0.01283967],"genre_scores_gemma":[0.9947102,5.805037e-7,0.004941987,0.0002261703,0.000003128992,8.223603e-7,0.000001648353,0.000001033993,0.0001144317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9769208,"threshold_uncertainty_score":0.06967942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02090702350349531,"score_gpt":0.2520330547288985,"score_spread":0.2311260312254032,"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."}}