{"id":"W4313494085","doi":"10.1038/s41467-022-35766-5","title":"Toward the design of ultrahigh-entropy alloys via mining six million texts","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"High Entropy Alloys Studies","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Army Research Office; Office of Science; Division of Materials Research; Oak Ridge National Laboratory; York University; U.S. Department of Energy; National Science Foundation","keywords":"Computer science; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003011852,0.0001586906,0.0001926642,0.0001276546,0.0002511188,0.00002024748,0.00122141,0.0001768626,0.00001395661],"category_scores_gemma":[0.0002133596,0.0001238594,0.00007919761,0.0007827053,0.000148584,0.00007684923,0.0002426516,0.0006466123,0.00008857596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000043033,"about_ca_system_score_gemma":0.00001588925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008773279,"about_ca_topic_score_gemma":0.00007802042,"domain_scores_codex":[0.9989878,0.0001565569,0.0002705894,0.0001201268,0.0002132104,0.0002517207],"domain_scores_gemma":[0.9973511,0.001089034,0.00005860848,0.001354593,0.0001073891,0.00003929993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006380166,0.0003612055,0.006391929,0.0003409469,0.002254552,0.00001916847,0.04526933,0.24481,0.3212601,0.0565282,0.3131543,0.009546419],"study_design_scores_gemma":[0.002046285,0.0002197505,0.08343987,0.0004225598,0.0005811279,0.00004103237,0.005432264,0.4993171,0.03338263,0.002957358,0.3704598,0.0017002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3006645,0.2532119,0.2556642,0.1199529,0.01036218,0.009793046,0.0006408183,0.01615346,0.03355715],"genre_scores_gemma":[0.9839448,0.004593981,0.0110725,0.00006861761,0.0000543191,0.00008674576,0.00005182046,0.0000394713,0.00008770043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6832804,"threshold_uncertainty_score":0.505084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03420276278444992,"score_gpt":0.2731853289048031,"score_spread":0.2389825661203532,"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."}}