{"id":"W4409158760","doi":"10.1038/s41597-025-04852-w","title":"StoichLife: A Global Dataset of Plant and Animal Elemental Content","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada; National Science Foundation; Royal Society; Department of Education and Training; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Vlaamse regering; Fonds Wetenschappelijk Onderzoek; Ministério da Ciência, Tecnologia e Inovação; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Deutsche Forschungsgemeinschaft; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Russian Science Foundation","keywords":"Content (measure theory); Information retrieval; Environmental science; Computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006196517,0.001001516,0.001029844,0.004624311,0.0005832929,0.001437932,0.001430948,0.001151449,0.009463879],"category_scores_gemma":[0.002947132,0.0004608607,0.000973599,0.007357756,0.000378615,0.001431393,0.001943272,0.0009898419,0.00973182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006908581,"about_ca_system_score_gemma":0.001062021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084675,"about_ca_topic_score_gemma":0.02292277,"domain_scores_codex":[0.9993212,0.00007536929,0.00009179595,0.0002933031,0.0001486858,0.00006954749],"domain_scores_gemma":[0.9984102,0.0002821749,0.00041667,0.000357437,0.0003789534,0.0001544555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007764422,0.0001859267,0.1633082,0.007653697,0.001145718,0.0006029456,0.001320085,0.005791552,0.01625887,0.008729263,0.7112622,0.08296505],"study_design_scores_gemma":[0.0001042114,0.00004165879,0.1051271,0.0003802607,0.0001294794,0.0003194351,0.0002846462,0.001683691,0.002059867,0.003348534,0.8864354,0.0000855839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.009544913,0.0005646971,0.00127029,0.00007513037,0.00002281502,0.00001844965,0.9853417,0.0008526042,0.002309461],"genre_scores_gemma":[0.01117803,0.0002895476,0.004201991,0.00006479469,0.00001356159,0.00009202388,0.9833145,0.0001962697,0.0006492865],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01084675,"threshold_uncertainty_score":0.03165984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04010059842137004,"score_gpt":0.2917755226563082,"score_spread":0.2516749242349381,"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."}}