{"id":"W2154227688","doi":"","title":"Linear Response for Approximate Inference","year":2003,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Belief propagation; Inference; Algorithm; Approximate inference; Factor graph; Computer science; Graph; Mathematics; Mathematical optimization; Theoretical computer science; Artificial intelligence; Decoding methods","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":[0.003515652,0.001055075,0.00132624,0.001076878,0.0006280545,0.001816188,0.00189714,0.002182794,0.01032828],"category_scores_gemma":[0.03030852,0.0005437179,0.000734232,0.002360013,0.001510365,0.002555151,0.00195737,0.003008524,0.004086222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261989,"about_ca_system_score_gemma":0.001478332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004409521,"about_ca_topic_score_gemma":0.002759544,"domain_scores_codex":[0.9959238,0.00209486,0.0001303021,0.0005974462,0.001016987,0.0002366321],"domain_scores_gemma":[0.9877194,0.009267833,0.0003767491,0.001534048,0.001014535,0.0000874405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003843556,0.00008653124,0.0006108985,0.0004292569,0.0001654204,0.0001707785,0.0001387758,0.4004709,0.003567478,0.273281,0.01506652,0.305628],"study_design_scores_gemma":[0.00002523313,0.00002775873,0.00008772541,0.00002215283,0.00001300896,0.0000438012,0.00001584756,0.8851944,0.001442634,0.1090685,0.004042794,0.00001614745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001270414,0.0004073411,0.9956399,0.0004267197,0.00007065538,0.00002696558,0.00006990518,0.0006097631,0.001478333],"genre_scores_gemma":[0.285123,0.001713407,0.6978567,0.001120297,0.0005658477,0.0007657994,0.0009288476,0.0004933326,0.01143269],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01032828,"threshold_uncertainty_score":0.03455156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03924093114696837,"score_gpt":0.3249770939864753,"score_spread":0.2857361628395069,"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."}}