{"id":"W2080375724","doi":"10.1088/1742-6596/95/1/012020","title":"Optimization and thermodynamics of classical problems from a quantum perspective","year":2008,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Quantum thermodynamics; Perspective (graphical); Quantum; Thermodynamics; Statistical physics; Theoretical physics; Physics; Quantum mechanics; Computer science; Artificial intelligence","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":[0.00008413737,0.0001111652,0.0002607722,0.00004498785,0.00008924592,0.00005396835,0.0003266553,0.00003877943,0.000002224181],"category_scores_gemma":[0.00002775811,0.00008590857,0.00006632537,0.0001585965,0.0001962796,0.0004718657,0.000105843,0.0002160192,2.477012e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001820343,"about_ca_system_score_gemma":0.0001938576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000242255,"about_ca_topic_score_gemma":0.000002086953,"domain_scores_codex":[0.9991862,0.00005701002,0.0002612395,0.0001416545,0.0002413084,0.0001126286],"domain_scores_gemma":[0.998843,0.00007555234,0.0003851932,0.0001482296,0.0004901635,0.00005789641],"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":[0.00006452177,0.0003015783,0.0005638522,0.00003331765,0.0001685173,0.0000484318,0.03430999,0.1978879,0.009251461,0.7059888,0.00003742934,0.05134419],"study_design_scores_gemma":[0.0002607663,0.0003801865,0.001483973,0.00008330506,0.00000983487,0.00009990267,0.0003361108,0.8582755,0.003016232,0.1359292,0.00001445397,0.000110511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2173217,0.0001057986,0.7816416,0.0006657362,0.0001129983,0.00003651315,0.000003844879,0.0000124341,0.00009940169],"genre_scores_gemma":[0.925341,0.0001388537,0.07437178,0.00001740249,0.0001157594,4.084445e-7,6.10736e-7,0.000005543301,0.000008615663],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7080193,"threshold_uncertainty_score":0.350325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704158206929635,"score_gpt":0.2233242901871909,"score_spread":0.2062827081178946,"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."}}