{"id":"W2160129920","doi":"10.1109/isit.2006.261908","title":"On Generalized Survey Propagation: Normal Realization and Sum-Product Interpretation","year":2006,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Formalism (music); Belief propagation; Markov random field; Computer science; Algorithm; Markov chain; Theoretical computer science; Mathematics; Discrete mathematics; Artificial intelligence; Decoding methods; Machine learning; Segmentation; Image segmentation","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":[0.003896943,0.0008533977,0.001499893,0.00233879,0.001789289,0.004495061,0.002353879,0.001987548,0.005309875],"category_scores_gemma":[0.01128806,0.0008005808,0.002171059,0.004279793,0.006452096,0.009870755,0.00389983,0.004022646,0.000732467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002159963,"about_ca_system_score_gemma":0.001816854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004088002,"about_ca_topic_score_gemma":0.003358611,"domain_scores_codex":[0.9968689,0.001274876,0.0001701705,0.0006662909,0.000695741,0.0003239618],"domain_scores_gemma":[0.993973,0.003600975,0.000436545,0.001041942,0.0006925453,0.0002549766],"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":[0.000008010318,0.000005896251,0.00008584827,0.00002021766,0.000006228312,0.00001845437,0.00007795476,0.003975341,0.0001141101,0.9909652,0.0004652899,0.004257457],"study_design_scores_gemma":[0.000004689562,0.00000614629,0.00004095603,0.000008900166,0.000005191208,0.00002213717,0.00002207917,0.02959717,0.0001125739,0.9686979,0.001472658,0.000009599496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01153606,0.0005540458,0.9723585,0.001288425,0.0001036443,0.00006053122,0.0002738239,0.0002020808,0.01362285],"genre_scores_gemma":[0.5629645,0.002452596,0.4149122,0.001257235,0.0008097489,0.0006728821,0.00118129,0.0004225173,0.01532698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005309875,"threshold_uncertainty_score":0.0206092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107111076637974,"score_gpt":0.2293821648430887,"score_spread":0.2183110540767089,"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."}}