{"id":"W4401206558","doi":"10.3390/agronomy14081700","title":"Interpolation of Nitrogen Fertilizer Use in Canada from Fertilizer Use Surveys","year":2024,"lang":"en","type":"article","venue":"Agronomy","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Fertilizer; Environmental science; Nitrogen; Nitrogen fertilizer; Interpolation (computer graphics); Agronomy; Chemistry; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001265381,0.0001079451,0.0001230149,0.00003469416,0.00001689181,0.00004686056,0.0001256971,0.00003693072,0.0003819018],"category_scores_gemma":[0.00001765856,0.00009444972,0.00003798895,0.0001737455,0.00004265099,0.000512208,0.0001072209,0.00008526588,0.00007030716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004566812,"about_ca_system_score_gemma":0.00006616044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9735189,"about_ca_topic_score_gemma":0.8889287,"domain_scores_codex":[0.9990873,0.00009457921,0.0002327157,0.0002512829,0.0001543977,0.0001797021],"domain_scores_gemma":[0.9995617,0.0001582701,0.00002907951,0.0001883637,0.000004669108,0.0000578798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001354772,0.00001556738,0.9966154,0.000003222823,0.00001183757,0.000009664614,0.0001770311,0.0002265089,0.0001416934,0.000009000256,0.0006003076,0.002176239],"study_design_scores_gemma":[0.0001444271,0.000006282832,0.9813352,0.00003053172,0.000009239604,4.702077e-7,0.00005057958,0.01471883,0.0005034421,0.001468959,0.001615498,0.0001165477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988376,0.0000563992,0.0004102832,0.00004925882,0.0001837507,0.0001089317,0.0000481149,0.00001668464,0.0002889447],"genre_scores_gemma":[0.9993308,0.000005781213,0.0003521216,0.00004792261,0.000009758201,0.000009113008,0.00007221686,0.00001254928,0.0001597403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08459028,"threshold_uncertainty_score":0.4181557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557859399521625,"score_gpt":0.1945872964190405,"score_spread":0.1790087024238243,"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."}}