{"id":"W3202197574","doi":"","title":"Assessing links between groundwater gaining areas and stream nutrient status in agricultural streams in the upper Thames River watershed, Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"STREAMS; Watershed; Groundwater; Water resource management; Agriculture; Hydrology (agriculture); Environmental science; Nutrient; Geography; Ecology; Archaeology; Geology","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":[0.0006184923,0.0002658189,0.0002638137,0.001001197,0.001945136,0.001582249,0.0008220749,0.0003955957,0.001147957],"category_scores_gemma":[0.002719406,0.0002354679,0.0003550966,0.00271764,0.0008708245,0.000397028,0.0006682605,0.0004333645,0.0001335786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02428953,"about_ca_system_score_gemma":0.02768347,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961888,"about_ca_topic_score_gemma":0.9990529,"domain_scores_codex":[0.9994568,0.00008143088,0.00004534615,0.00009944783,0.0001598633,0.0001570034],"domain_scores_gemma":[0.9975882,0.0004470996,0.000321641,0.00005773183,0.00119138,0.0003939628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000100163,0.00003625893,0.9911948,0.00003420972,0.00007860814,0.0000883231,0.00116847,0.0008208273,0.0003299026,0.0001906997,0.0007726646,0.005185053],"study_design_scores_gemma":[0.000007164276,0.00001810697,0.9948584,0.00001974741,0.00003595369,0.00002144014,0.002848186,0.001167257,0.00008490658,0.00005821703,0.0008730215,0.000007658919],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967764,0.000164356,0.0001287563,0.0001380061,0.000003934922,0.00002835312,0.001243311,0.000005450901,0.001511453],"genre_scores_gemma":[0.9975681,0.0001769263,0.0002766238,0.00003053156,0.000002172554,0.00001181887,0.0006698405,0.000002655256,0.001261436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02428953,"threshold_uncertainty_score":0.1762337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01325925623596559,"score_gpt":0.2186447961005364,"score_spread":0.2053855398645708,"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."}}