{"id":"W2119752000","doi":"10.2134/agronj2008.0172x","title":"Leaf Nitrogen Concentration as an Indicator of Corn Nitrogen Status","year":2009,"lang":"en","type":"article","venue":"Agronomy Journal","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Association of Friendship Centres; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Nitrogen; Human fertilization; Poaceae; Zea mays; Sampling (signal processing); Shoot; Growing season; Nitrogen fertilizer; Sampling time; Agronomy; Biology; Animal science; Fertilizer; Botany; Horticulture; Chemistry; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000371358,0.0002432799,0.0002256512,0.0005422416,0.0002203747,0.0002949366,0.0001758185,0.000272588,0.0005824116],"category_scores_gemma":[0.0004733038,0.0001449924,0.000105504,0.0004040227,0.0001545851,0.0002131453,0.0001915986,0.0002664929,0.0001246855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007888238,"about_ca_system_score_gemma":0.0002130669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0161137,"about_ca_topic_score_gemma":0.04299573,"domain_scores_codex":[0.9997641,0.00004246667,0.00001364548,0.0000751007,0.00008171843,0.00002299077],"domain_scores_gemma":[0.9995636,0.0001113485,0.0001356113,0.00002579811,0.00009228331,0.00007137844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003700898,0.00008660156,0.6494261,0.00005698127,0.00006070063,0.00004418516,0.0001517984,0.000505004,0.3414838,0.00002941778,0.00009247923,0.007692783],"study_design_scores_gemma":[0.000002033728,0.00012508,0.9912719,0.000001633204,0.000007011156,0.00002666466,0.00003795994,0.0005618058,0.007805176,0.00000919814,0.0001481221,0.000003375205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985955,0.0001433619,0.0005507672,0.000004949148,0.000001913911,0.000007346994,0.0001980927,0.0000110048,0.0004870085],"genre_scores_gemma":[0.9965751,0.0001052295,0.001521606,0.0000303826,0.000002575197,0.0000178773,0.0007970113,0.000006197497,0.0009440012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0161137,"threshold_uncertainty_score":0.03203982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01195361260554171,"score_gpt":0.2280828900643761,"score_spread":0.2161292774588344,"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."}}