{"id":"W4416051513","doi":"10.48550/arxiv.2508.15759","title":"Belief Propagation TNS data sets","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Office of Science; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; U.S. Department of Energy","keywords":"Scaling; Quantum; Quantum annealing; Quantum algorithm; Quantum process; Quantum system; Measure (data warehouse)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005573655,0.00155342,0.001358775,0.003875921,0.00150361,0.00346211,0.002975115,0.002978507,0.008135402],"category_scores_gemma":[0.03834736,0.0005415528,0.001721055,0.003453509,0.001697268,0.003909554,0.002156528,0.00405311,0.005316276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002431165,"about_ca_system_score_gemma":0.002810796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01370654,"about_ca_topic_score_gemma":0.0153401,"domain_scores_codex":[0.9942968,0.001583494,0.000643163,0.001133926,0.001944982,0.0003977069],"domain_scores_gemma":[0.9805649,0.01014559,0.0007832934,0.004312756,0.003758027,0.000435496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003276285,0.001256454,0.02662655,0.002019032,0.000832025,0.0009688145,0.0006399178,0.3979974,0.006074165,0.05002452,0.1738319,0.336453],"study_design_scores_gemma":[0.0001304498,0.0002167878,0.002695556,0.0001338793,0.00007628556,0.0003746379,0.0002075407,0.9124738,0.007162552,0.05573749,0.02072238,0.00006861121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.2137713,0.003580876,0.5028608,0.009458669,0.001999197,0.001912213,0.2305317,0.01264381,0.02324137],"genre_scores_gemma":[0.5564349,0.0008729791,0.2282166,0.0009529295,0.000401143,0.001382598,0.2042902,0.0005133759,0.006935322],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01370654,"threshold_uncertainty_score":0.0294767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05558772314621373,"score_gpt":0.3014525651439273,"score_spread":0.2458648419977136,"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."}}