{"id":"W2085148121","doi":"10.1063/1.1940028","title":"Asynchronous multicanonical basin hopping method and its application to cobalt nanoclusters","year":2005,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Asynchronous communication; Nanoclusters; Computer science; Monte Carlo method; Message Passing Interface; Computational science; Interface (matter); Parallel computing; Statistical physics; Message passing; Physics; Materials science; Nanotechnology; Mathematics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775844,0.0001226047,0.0002519347,0.0000210329,0.00008748799,0.00005963735,0.0005326365,0.00004335777,0.00004127524],"category_scores_gemma":[0.0003404233,0.00008197127,0.00004313811,0.0001392476,0.00009861417,0.0002156192,0.0001791713,0.0002059076,0.00007175374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008936041,"about_ca_system_score_gemma":0.00006233419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000862343,"about_ca_topic_score_gemma":4.142063e-7,"domain_scores_codex":[0.9986186,0.0002154432,0.0003844133,0.0001550923,0.0003879186,0.0002385076],"domain_scores_gemma":[0.9987925,0.0004177982,0.0003071067,0.0001911166,0.0001314499,0.0001600331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006483462,0.00003252416,0.00001030984,0.00001216835,0.000003387155,4.555482e-7,0.0003664256,0.009532243,0.9843244,0.0004179001,0.0001080702,0.005127282],"study_design_scores_gemma":[0.0002520894,0.00005773209,0.0000938293,0.00003443082,0.00003036939,0.0000799693,0.00001791438,0.02671056,0.9710183,0.0008266863,0.0007639647,0.0001142018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7895934,0.00004717954,0.2071966,0.002825755,0.00009676151,0.0001176736,0.000002357747,0.00001593044,0.0001043594],"genre_scores_gemma":[0.9351734,0.000006386261,0.06335011,0.0009014416,0.0005459308,0.000002537131,2.888615e-7,0.00001176616,0.000008145374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.14558,"threshold_uncertainty_score":0.3342691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066953083559043,"score_gpt":0.2968175190312939,"score_spread":0.2861479881957035,"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."}}