{"id":"W3177619806","doi":"10.1088/2515-7620/ac13c6","title":"Integrated farm management systems to improve nutrient management using semi-virtual Farmlets: agronomic responses","year":2021,"lang":"en","type":"article","venue":"Environmental Research Communications","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Agriculture and Agri-Food Canada","funders":"","keywords":"Environmental science; Manure; Irrigation; Agronomy; Agriculture; Nutrient management; Manure management; Production (economics); Productivity; Agricultural engineering; Agricultural science; Business; Engineering; Geography","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00115437,0.0002857392,0.000238295,0.0002420828,0.0009579633,0.0002191563,0.001751741,0.00009354188,0.0002441325],"category_scores_gemma":[0.00003581501,0.0002948362,0.0001052023,0.0007989645,0.0006538588,0.0001967638,0.006876912,0.0005361324,0.001773809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002996088,"about_ca_system_score_gemma":0.00002608518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004032007,"about_ca_topic_score_gemma":0.00004273163,"domain_scores_codex":[0.9959137,0.0008862552,0.0005179934,0.000784573,0.001070729,0.0008267023],"domain_scores_gemma":[0.9964349,0.0002219065,0.00008077159,0.002869569,0.00001597818,0.0003768216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00184943,0.01986151,0.3134307,0.0003949056,0.002236961,0.001345709,0.01019251,0.05351964,0.214409,0.06233168,0.01469592,0.3057321],"study_design_scores_gemma":[0.003608727,0.000701592,0.07305747,0.0004473603,0.0002071199,0.0001010312,0.05130685,0.07208336,0.006908729,0.004342599,0.7853036,0.001931586],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769827,0.0004983665,0.003317236,0.0009277863,0.000258662,0.001621566,0.0002018667,0.00008394542,0.01610792],"genre_scores_gemma":[0.9775564,0.002110248,0.008067345,0.0001696963,0.00002626424,0.0005065849,0.0002612524,0.00005558987,0.01124662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7706077,"threshold_uncertainty_score":0.9999503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0496654915848497,"score_gpt":0.3194017415827622,"score_spread":0.2697362499979125,"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."}}