{"id":"W2157460957","doi":"10.1890/13-2276.1","title":"You are not always what we think you eat: selective assimilation across multiple whole‐stream isotopic tracer studies","year":2014,"lang":"en","type":"article","venue":"Ecology","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Oak Ridge National Laboratory; Biological and Environmental Research; UT-Battelle; Battelle; U.S. Department of Energy; Office of Science; National Science Foundation","keywords":"Food web; TRACER; Trophic level; Detritus; Ecology; Abundance (ecology); Stable isotope ratio; Food chain; Environmental chemistry; Isotope analysis; Environmental science; Primary producers; Ecological stoichiometry; Invertebrate; Assimilation (phonology); Biology; Chemistry; Ecosystem; Nutrient; Phytoplankton","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006508914,0.0002785188,0.0005364772,0.00006279974,0.0004963851,0.00006007725,0.0003733331,0.0003128479,0.001097462],"category_scores_gemma":[0.0006299168,0.0002539386,0.0001291437,0.000288287,0.0005011273,0.0006105282,0.0004023827,0.000319773,0.002119748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005324205,"about_ca_system_score_gemma":0.00001285808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000563033,"about_ca_topic_score_gemma":0.01445618,"domain_scores_codex":[0.9975764,0.0003713985,0.0004068061,0.0007237695,0.000223663,0.000697981],"domain_scores_gemma":[0.9985353,0.0005875318,0.0002854549,0.0004550037,0.00004791674,0.00008873276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004644319,0.0002790989,0.9551209,0.000012795,0.0002095916,0.00001921987,0.009683845,0.006010634,0.002424308,0.00005363331,0.009015981,0.01712357],"study_design_scores_gemma":[0.0009345257,0.0003150426,0.9545955,0.00001059139,0.00007759015,0.00001413354,0.004481549,0.005891754,0.003083684,0.001494159,0.02876417,0.0003373143],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902979,0.0001389736,0.0002652692,0.005728649,0.0009856154,0.0004238308,0.00001102612,0.00009971187,0.002049076],"genre_scores_gemma":[0.9930705,0.0002633936,0.0007373434,0.001933938,0.0001875122,0.0001263278,0.00001570532,0.00002688116,0.003638363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01974818,"threshold_uncertainty_score":0.9999913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975899762485391,"score_gpt":0.2769049729450801,"score_spread":0.2571459753202262,"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."}}