{"id":"W4297312334","doi":"10.3389/fpls.2022.994306","title":"Enhancement of nitrogen use efficiency through agronomic and molecular based approaches in cotton","year":2022,"lang":"en","type":"review","venue":"Frontiers in Plant Science","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Zhejiang Academy of Agricultural Sciences","keywords":"Production (economics); Agronomy; Sustainability; Agriculture; Cropping; Biotechnology; Fertilizer; Profitability index; Nutrient; Business; Agricultural engineering; Environmental science; Biology; Engineering; Economics","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":[0.0009001114,0.0002785674,0.0009452187,0.0001661058,0.0001188477,0.00005366741,0.0007692033,0.0001082891,0.0000254609],"category_scores_gemma":[0.00007575375,0.0001264259,0.0001226388,0.001423949,0.0003476855,0.0002358747,0.0002005551,0.0002587113,0.000001148627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001296791,"about_ca_system_score_gemma":0.0001367915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001486251,"about_ca_topic_score_gemma":0.00002485728,"domain_scores_codex":[0.9976602,0.0001641762,0.0005422006,0.0007116289,0.000441111,0.0004807168],"domain_scores_gemma":[0.9993171,0.0001816719,0.0002969404,0.000118432,0.000009160074,0.00007665813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003595739,0.0003916287,0.00251053,0.0006026783,0.00001638653,0.00005175383,0.0002083835,0.00002538035,0.001087917,0.0005792672,0.0003493122,0.9941408],"study_design_scores_gemma":[0.0001655795,0.00009702711,0.0003076792,0.0008480613,0.00005210868,0.00001086218,0.0001634662,0.0003144926,0.000463292,0.0001275409,0.9970857,0.0003642236],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.09270124,0.9054949,0.00006424898,0.00001361369,0.0004073474,0.0007302461,0.0004094516,0.00001030791,0.0001686841],"genre_scores_gemma":[0.002943407,0.9954274,0.001191355,0.00003974715,0.00001624782,0.00008593516,0.000277431,0.000001663961,0.00001676926],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9967363,"threshold_uncertainty_score":0.51555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0687179768968041,"score_gpt":0.2426882315779085,"score_spread":0.1739702546811044,"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."}}