{"id":"W4288788916","doi":"10.1002/ael2.20084","title":"Addressing conservation practice limitations and trade‐offs for reducing phosphorus loss from agricultural fields","year":2022,"lang":"en","type":"article","venue":"Agricultural & Environmental Letters","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Manitoba","funders":"Natural Resources Conservation Service","keywords":"Watershed; Conservation agriculture; Environmental science; Agriculture; Sustainability; Wetland; Soil conservation; Sediment; Environmental resource management; Natural resource economics; Agroforestry; Ecology; Economics; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001075426,0.0002204252,0.0001522316,0.00001538682,0.0008037899,0.00008135137,0.0001798254,0.00005324538,0.00008207585],"category_scores_gemma":[0.00002501132,0.0001690114,0.00008914564,0.0001221211,0.0001580071,0.0006668954,0.0002443654,0.000236008,0.0000198871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003944802,"about_ca_system_score_gemma":0.000002074805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005729271,"about_ca_topic_score_gemma":0.000008763747,"domain_scores_codex":[0.9984915,0.00009571638,0.0002585567,0.0004733825,0.0003611759,0.0003196626],"domain_scores_gemma":[0.9993054,0.0002968964,0.0001670075,0.0001281808,0.000001601562,0.0001009136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003859554,0.001005546,0.447914,0.0000221619,0.0002804579,0.00007772914,0.0175171,0.03174577,0.3635702,0.0001343282,0.1131319,0.02421488],"study_design_scores_gemma":[0.001041345,0.000169078,0.9539604,0.00001243684,0.0001395961,0.0001136334,0.007330557,0.0008280423,0.00203377,0.000153046,0.03367396,0.0005441086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740025,0.0001180079,0.00008593473,0.02465787,0.000266834,0.0004578597,0.0001667859,0.00004522727,0.000199009],"genre_scores_gemma":[0.9904415,0.00007073128,0.002112736,0.006049064,0.00009520098,0.0001806611,0.0009259706,0.0000139587,0.0001101793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5060464,"threshold_uncertainty_score":0.6892083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229145179571692,"score_gpt":0.213409840810125,"score_spread":0.1911183890144081,"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."}}