{"id":"W6925563072","doi":"10.17632/zjv2264cky.1","title":"Dietary contribution of three food sources to macroinvertebrates calculated using stable isotopes","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stable isotope ratio; Invertebrate; STREAMS; Isotope; Isotope analysis; δ15N; Hydrology (agriculture); δ13C","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001037363,0.0007141652,0.0007238486,0.002741371,0.0006068939,0.0008200259,0.0008258731,0.0003900054,0.006335558],"category_scores_gemma":[0.002181601,0.0003850735,0.0006258502,0.004812104,0.0002658143,0.0002910619,0.0009282287,0.0005632185,0.003079175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003023756,"about_ca_system_score_gemma":0.003138982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3332964,"about_ca_topic_score_gemma":0.5088306,"domain_scores_codex":[0.999447,0.00006122631,0.00007946664,0.0001721685,0.0001346063,0.000105454],"domain_scores_gemma":[0.998908,0.0001498506,0.0001682805,0.0001208735,0.0005738601,0.00007909633],"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":[0.00119905,0.0001550844,0.4522835,0.003177695,0.000860878,0.0002616406,0.0007453845,0.002833117,0.005881045,0.001428281,0.4973411,0.0338332],"study_design_scores_gemma":[0.0003772324,0.00003769862,0.7193514,0.0003410654,0.0002509677,0.00009599855,0.0005115837,0.00145776,0.001672223,0.0005671441,0.2752807,0.00005622437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02245084,0.0001014407,0.0002200303,0.00004720576,0.00001346337,0.0000575156,0.9759524,0.00006857546,0.001088514],"genre_scores_gemma":[0.02314487,0.000120099,0.001182807,0.00004547146,0.000006084548,0.0002889374,0.9734333,0.00003921052,0.00173923],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3332964,"threshold_uncertainty_score":0.6627128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04898100708168896,"score_gpt":0.3081954612329971,"score_spread":0.2592144541513082,"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."}}