{"id":"W2403968605","doi":"","title":"Graph cuts is a max-product algorithm","year":2011,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Counterexample; Mathematics; Fixed point; Graph; Discrete mathematics; Mathematical optimization; Algorithm; Combinatorics; Mathematical analysis","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":[0.0002492271,0.0001282207,0.000114391,0.0001453637,0.00006954993,0.00005084203,0.00109866,0.00003932532,0.0001482693],"category_scores_gemma":[0.00002103329,0.0001117436,0.00006874575,0.0004863777,0.000032974,0.0003876112,0.0003289015,0.0001236623,0.0002057146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001674246,"about_ca_system_score_gemma":0.00002895932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004549338,"about_ca_topic_score_gemma":0.00001654684,"domain_scores_codex":[0.9988783,0.00003042493,0.0001541384,0.0004715081,0.0001986298,0.0002670035],"domain_scores_gemma":[0.9987933,0.00001739725,0.0000522886,0.0009737394,0.00009005083,0.00007324029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000217581,0.0001511665,0.001927133,0.000008792143,0.00002400981,0.00006506913,0.006054909,8.499224e-8,0.0007736094,0.03192404,0.08063307,0.878436],"study_design_scores_gemma":[0.0003129678,0.0004535649,0.006460764,0.00005179863,0.00001698116,0.0003928869,0.0001068092,0.02172206,0.7321815,0.209488,0.02759185,0.001220853],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001210152,0.00006241025,0.9167703,0.0003896142,0.0004934127,0.0001196182,5.04287e-7,0.002003577,0.07895046],"genre_scores_gemma":[0.0937109,0.00001127683,0.9019955,0.001077328,0.00004550728,0.00001561951,2.285266e-7,0.00001158429,0.003132077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8772151,"threshold_uncertainty_score":0.455677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04111402592383154,"score_gpt":0.2516757869069481,"score_spread":0.2105617609831165,"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."}}