{"id":"W4384263497","doi":"10.48550/arxiv.2307.05691","title":"KPM: A Flexible and Data-Driven K-Process Model for Nucleosynthesis","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; National Astronomical Observatories, Chinese Academy of Sciences; University of Illinois at Urbana-Champaign; Max-Planck-Institut für Astronomie; University of Colorado Boulder; Leibniz-Institut für Astrophysik Potsdam; New Mexico State University; Nanjing University; China National Textile and Apparel Council; National Science Foundation; Yunnan University; Yale University; University of Toronto; École Polytechnique Fédérale de Lausanne; Deutsche Forschungsgemeinschaft; Space Telescope Science Institute; Universidad Nacional Autónoma de México; Alfred P. Sloan Foundation; Johns Hopkins University; Carnegie Institution of Washington; University of Utah; Harvard University; Ohio State University; Smithsonian Astrophysical Observatory; Flatiron Health; Smithsonian Institution","keywords":"Astrophysics; Physics; Metallicity; Stars; Nucleosynthesis; Milky Way; Abundance (ecology); Galaxy; Astronomy; Range (aeronautics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001039485,0.001091006,0.001044511,0.0007720463,0.001045857,0.002295454,0.004983956,0.002280946,0.004457621],"category_scores_gemma":[0.003547759,0.001042994,0.002552275,0.001082194,0.001156671,0.002770544,0.001761452,0.001915932,0.001707263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001645795,"about_ca_system_score_gemma":0.001555018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01591554,"about_ca_topic_score_gemma":0.007238151,"domain_scores_codex":[0.9996731,0.00008888495,0.00002146012,0.0001022868,0.00005992214,0.00005435272],"domain_scores_gemma":[0.9991503,0.0003911262,0.0001309869,0.000117354,0.000112436,0.00009775921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001677128,0.00004985013,0.006265988,0.0001004088,0.0001199822,0.0003123651,0.0001830964,0.9318812,0.001946062,0.05059116,0.001624874,0.006757358],"study_design_scores_gemma":[0.00007445254,0.00002863896,0.000910189,0.000009871587,0.00002711431,0.0001320085,0.00002387964,0.9639021,0.0002926402,0.03191385,0.002650254,0.00003499548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2902814,0.001060589,0.6669602,0.002407675,0.0003593942,0.0003154151,0.005886374,0.002606819,0.03012219],"genre_scores_gemma":[0.9054924,0.0005500391,0.07721208,0.0005113587,0.0001621882,0.0006093922,0.002027784,0.0005875818,0.01284714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01591554,"threshold_uncertainty_score":0.03164583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1632808689935493,"score_gpt":0.2398228750589871,"score_spread":0.07654200606543787,"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."}}