{"id":"W2021047379","doi":"10.1007/s11270-013-1643-9","title":"Relating P Lability in Stream Sediments to Watershed Land Use via an Effective Sequential Extraction Scheme","year":2013,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Deutscher Akademischer Austauschdienst","keywords":"Lability; Extraction (chemistry); Sediment; Environmental science; Watershed; Soil water; Aqua regia; Eutrophication; Hydrology (agriculture); Agricultural land; Manure; Land use; Environmental chemistry; Chemistry; Soil science; Agronomy; Ecology; Geology; Biology; Nutrient","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005342588,0.0002463977,0.0003086304,0.0007040496,0.0002499884,0.0003125881,0.0003643809,0.0002223502,0.0004526383],"category_scores_gemma":[0.001473804,0.0001818285,0.0002684268,0.0007742816,0.0002972647,0.0005814125,0.000376588,0.000175437,0.00009441597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000525969,"about_ca_system_score_gemma":0.0005391542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004804162,"about_ca_topic_score_gemma":0.007907003,"domain_scores_codex":[0.9998034,0.00003385258,0.00002536372,0.00005814579,0.00005751832,0.0000216457],"domain_scores_gemma":[0.9994282,0.0002258193,0.000109953,0.00009780171,0.0001204421,0.00001766216],"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":[0.002791906,0.0003969896,0.08634354,0.0002164175,0.0001814879,0.0001364086,0.0001658663,0.298661,0.371443,0.004948118,0.0003704342,0.2343449],"study_design_scores_gemma":[0.00005453512,0.0003649204,0.03533059,0.00000742305,0.00008720325,0.00009437115,0.00002846137,0.7701653,0.1906466,0.002355083,0.0008246115,0.00004098113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861812,0.0001245114,0.1364045,0.00004272275,0.00001138635,0.00007432939,0.0002916016,0.0001651295,0.001073832],"genre_scores_gemma":[0.9618691,0.00007630876,0.03715991,0.000008276009,0.000003736926,0.00003673512,0.0001477017,0.000007164194,0.0006909759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004804162,"threshold_uncertainty_score":0.009552419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008955180069749494,"score_gpt":0.2298632280454259,"score_spread":0.2209080479756764,"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."}}