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Record W3004432508 · doi:10.1093/jxb/eraa049

The intersection of nitrogen nutrition and water use in plants: new paths toward improved crop productivity

2020· review· en· W3004432508 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental Botany · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsApoplastNitrogenTranspirationEnvironmental scienceAgronomyWater transportProductivityCropWater useNitrateWater flowBiologyChemistryPhotosynthesisEnvironmental engineeringBotanyEcology

Abstract

fetched live from OpenAlex

Water and nitrogen availability limit crop productivity globally more than most other environmental factors. Plant availability of macronutrients such as nitrate is, to a large extent, regulated by the amount of water available in the soil, and, during drought episodes, crops can become simultaneously water and nitrogen limited. In this review, we explore the intricate relationship between water and nitrogen transport in plants, from transpiration-driven mass flow in the soil to uptake by roots via membrane transporters and channels and transport to aerial organs. We discuss the roles of root architecture and of suberized hydrophobic root barriers governing apoplastic water and nitrogen movement into the vascular system. We also highlight the need to identify the signalling cascades regulating water and nitrogen transport, as well as the need for targeted physiological analyses of plant traits influencing water and nitrogen uptake. We further advocate for incorporation of new phenotyping technologies, breeding strategies, and agronomic practices to improve crop yield in water- and nitrogen-limited production systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.270
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it