{"id":"W2058592805","doi":"10.1016/j.scitotenv.2014.11.100","title":"A multi-element screening method to identify metal targets for blood biomonitoring in green sea turtles ( Chelonia mydas )","year":2015,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Turtle Biology and Conservation","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; University of Queensland; Queensland Health; National Research Centre","keywords":"Biomonitoring; Environmental science; Certified reference materials; Environmental chemistry; Turtle (robot); Ecology; Biology; Chemistry","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":[0.0003490629,0.0005535782,0.0003052258,0.0007215872,0.0003433709,0.0002890768,0.0004084874,0.0006132977,0.0005868952],"category_scores_gemma":[0.000236851,0.0002623946,0.0003209968,0.0002039519,0.0001978432,0.0001529949,0.0004175508,0.0003571103,0.0003415086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001277517,"about_ca_system_score_gemma":0.0002459541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009791697,"about_ca_topic_score_gemma":0.002960898,"domain_scores_codex":[0.9997566,0.00003173698,0.00001616584,0.0000905694,0.00008088371,0.00002387651],"domain_scores_gemma":[0.9998291,0.00004330306,0.0000289998,0.00001389549,0.00006340999,0.00002139447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004804328,0.00002458875,0.0009963847,0.00003658832,0.00001126308,0.00002586891,0.00001560883,0.00005317668,0.9938505,0.00001474999,0.00004123374,0.004881894],"study_design_scores_gemma":[0.0000211138,0.0005952824,0.009895344,0.000008565474,0.0001168589,0.0005715723,0.00007245832,0.005309902,0.9815559,0.00005276716,0.001775609,0.00002471452],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8876718,0.001907841,0.1071555,0.0002397267,0.0001065401,0.0002082913,0.0005441186,0.000540784,0.001625366],"genre_scores_gemma":[0.8914704,0.0009196119,0.1008819,0.0002507415,0.00001773332,0.0001570562,0.0005322095,0.00003331015,0.005736951],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0009791697,"threshold_uncertainty_score":0.001963377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04249158461494801,"score_gpt":0.3110712117351012,"score_spread":0.2685796271201532,"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."}}