{"id":"W2897889941","doi":"10.1007/s10533-018-0502-6","title":"Watershed ‘chemical cocktails’: forming novel elemental combinations in Anthropocene fresh waters","year":2018,"lang":"en","type":"article","venue":"Biogeochemistry","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University; Brandon University; Agriculture and Agri-Food Canada","funders":"Division of Environmental Biology; U.S. Geological Survey; U.S. Department of Agriculture; U.S. Environmental Protection Agency","keywords":"Anthropocene; Watershed; Environmental science; Ecosystem; Earth science; Hydrology (agriculture); Geology; Ecology; Paleontology; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002035108,0.0001511044,0.000124711,0.0000247164,0.0001284321,0.0000327003,0.0002316581,0.0001040644,0.003096051],"category_scores_gemma":[0.00001605213,0.000141789,0.0000506917,0.0001712891,0.0004576252,0.0001526994,0.0002158288,0.0001107739,0.0003164232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003230787,"about_ca_system_score_gemma":0.00001307337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006469936,"about_ca_topic_score_gemma":0.00005555653,"domain_scores_codex":[0.9987438,0.00001747471,0.0002807293,0.0003207247,0.0002553104,0.0003819079],"domain_scores_gemma":[0.9995794,0.0000142928,0.00005976828,0.0002245723,0.000009481852,0.000112535],"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":[0.00001816721,0.0003981546,0.07234897,0.00001248229,0.000008807088,0.000003771347,0.000481275,0.000002460024,0.9222598,0.00007039082,0.004147007,0.0002486791],"study_design_scores_gemma":[0.0009955405,0.00003112394,0.009570866,0.00001735732,0.00000627247,0.00001040765,0.0003230598,0.0002020385,0.981168,0.0002918956,0.007160136,0.0002232715],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919018,0.000003375458,0.0001748138,0.001100372,0.0001086481,0.0001101826,0.00007596806,0.00004359262,0.006481271],"genre_scores_gemma":[0.9978032,0.000002654985,0.00137563,0.0002701057,0.00006866543,0.00001672142,0.0001923165,0.000009707961,0.0002609943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06277811,"threshold_uncertainty_score":0.9978153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964936041343318,"score_gpt":0.2730243542699259,"score_spread":0.2533749938564927,"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."}}