{"id":"W4408447369","doi":"10.1103/physrevapplied.23.034031","title":"Parallel tempering–inspired distributed binary optimization with in-memory computing","year":2025,"lang":"en","type":"article","venue":"Physical Review Applied","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Health Quality Council","funders":"Defense Advanced Research Projects Agency","keywords":"Computer science; Parallel computing; Binary number; Distributed computing; Mathematics; Arithmetic","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":[0.000212104,0.0001709288,0.0003714084,0.00005852911,0.0001093392,0.00004640179,0.0005078766,0.00002116246,0.000002651455],"category_scores_gemma":[0.00001741064,0.0001347394,0.00006349092,0.001232474,0.00005498805,0.0001258307,0.000194042,0.0001603288,0.00001401246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002935547,"about_ca_system_score_gemma":0.00004146887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002269773,"about_ca_topic_score_gemma":3.013522e-7,"domain_scores_codex":[0.99892,0.00006061469,0.0002335617,0.0003932007,0.0001538386,0.0002387716],"domain_scores_gemma":[0.9993077,0.0001098051,0.00008430559,0.000412114,0.00003255481,0.00005350941],"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":[0.00004279178,0.0007092822,0.0001236449,0.001632386,0.0000560451,0.00002927501,0.0002734771,0.1749878,0.0007161011,0.6759635,0.0002232145,0.1452425],"study_design_scores_gemma":[0.001348468,0.00009276179,0.002401076,0.003044088,0.00004737168,0.000003298233,0.00002619611,0.9704636,0.0006063205,0.02062525,0.0007931588,0.0005484177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009618799,0.001965588,0.9842457,0.0005150253,0.00005411993,0.0005706446,0.000001953821,0.000186104,0.002842121],"genre_scores_gemma":[0.9679132,0.0003467484,0.03061851,0.0009670048,0.00003197695,0.0000775414,0.0000231496,0.000008559028,0.00001335532],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9582943,"threshold_uncertainty_score":0.5494514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008125922655047454,"score_gpt":0.25451711806725,"score_spread":0.2463911954122026,"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."}}