{"id":"W2539427592","doi":"10.1186/s12870-016-0918-x","title":"Biosensor-based spatial and developmental mapping of maize leaf glutamine at vein-level resolution in response to different nitrogen rates and uptake/assimilation durations","year":2016,"lang":"en","type":"article","venue":"BMC Plant Biology","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Grain Farmers of Ontario; Ontario Ministry of Agriculture, Food and Rural Affairs; Government of Canada; Government of Ontario; Ministry of Agriculture, Food and Rural Affairs; University of Guelph","keywords":"Biology; Glutamine; Assimilation (phonology); Shoot; In situ; Amino acid; Nitrogen; Biophysics; Botany; Biochemistry; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001602847,0.0002609509,0.0002325797,0.0002163241,0.0001502876,0.0003374792,0.0004163371,0.0005443578,0.0005121076],"category_scores_gemma":[0.0001778345,0.0001709499,0.0002452001,0.0002992335,0.0002032032,0.0002510522,0.0002441523,0.0004150551,0.0002213503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008374981,"about_ca_system_score_gemma":0.0002501655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002655166,"about_ca_topic_score_gemma":0.00387963,"domain_scores_codex":[0.999851,0.000007135597,0.000004711451,0.00007392347,0.00003932398,0.00002379653],"domain_scores_gemma":[0.9998746,0.00002356057,0.00004233403,0.0000107597,0.00003282715,0.00001597121],"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":[0.000017005,0.000003235283,0.0001097122,0.00001050728,0.000001010249,0.000003416898,0.000008300043,0.00003926083,0.9992464,0.00002595081,0.00001130155,0.0005240008],"study_design_scores_gemma":[0.000008071112,0.00006589948,0.008361031,0.000003138843,0.00001049371,0.00005048937,0.00003812202,0.003416182,0.9870314,0.00008307927,0.0009180672,0.00001404623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619224,0.0007337111,0.03344562,0.0001343332,0.00003133566,0.00003730811,0.001533877,0.0003084581,0.001852906],"genre_scores_gemma":[0.9610271,0.0007783461,0.03434712,0.0001021922,0.00001100515,0.00009095194,0.0007941148,0.00006347876,0.002785568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002655166,"threshold_uncertainty_score":0.006076574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05206814766775481,"score_gpt":0.2304546816997358,"score_spread":0.178386534031981,"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."}}