{"id":"W4298127732","doi":"","title":"Overall multi-media persistence as an indicator of potential for population-level intake of \\nenvironmental contaminants","year":2003,"lang":"en","type":"article","venue":"University of North Texas Digital Library (University of North Texas)","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Lawrence Berkeley National Laboratory; U.S. Environmental Protection Agency; U.S. Department of Energy","keywords":"Persistence (discontinuity); Contamination; Environmental science; Population; Environmental health; Environmental chemistry; Biology; Ecology; Medicine; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0009633183,0.0002688399,0.0002314992,0.001069458,0.0002722018,0.0009352259,0.0005522151,0.0004056213,0.001086267],"category_scores_gemma":[0.002640086,0.0001345694,0.0003951171,0.0007039701,0.0005675036,0.00068986,0.0008700913,0.0004036175,0.00010551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00149731,"about_ca_system_score_gemma":0.0008384466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02967039,"about_ca_topic_score_gemma":0.03019209,"domain_scores_codex":[0.9995571,0.00005166219,0.00002385085,0.0001229528,0.0001765519,0.0000678537],"domain_scores_gemma":[0.9964607,0.001143223,0.00154311,0.0002497423,0.0004602679,0.0001428513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002662698,0.0001004567,0.9009731,0.0001202132,0.0002487009,0.0002969534,0.0003322914,0.03415714,0.03542625,0.001469323,0.0001824514,0.0264268],"study_design_scores_gemma":[0.000005489633,0.0007311791,0.9227976,0.00002391801,0.0001857885,0.0004774974,0.0006857273,0.0512934,0.0205577,0.00191249,0.001278764,0.00005038827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886013,0.0002592143,0.008128425,0.00006747051,0.000002111404,0.00002974596,0.0006209809,0.00004288842,0.002247905],"genre_scores_gemma":[0.9969577,0.0001291635,0.001959951,0.00001787521,0.000002171636,0.00001743993,0.0003620264,0.000003522753,0.0005501843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02967039,"threshold_uncertainty_score":0.05899537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127569080371127,"score_gpt":0.1861197830216428,"score_spread":0.1733628749845301,"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."}}