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Record W2163305000 · doi:10.1093/treephys/tpu005

Nitrogen uptake over entire root systems of tree seedlings

2014· article· en· W2163305000 on OpenAlexafffund
B. J. Hawkins, Samantha Robbins, Roy Porter

Bibliographic record

VenueTree Physiology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Forests, Lands and Natural Resource Operations
KeywordsBiomass (ecology)NitrogenBotanyRoot systemSeedlingFlux (metallurgy)Woody plantHorticultureBiologyAgronomyChemistry

Abstract

fetched live from OpenAlex

Uptake of nitrogen (N) by sequential root regions in six tree species was measured in roots of 16- to 26-month-old seedlings at 50 and 1500 µM NH4NO3 concentration, at the cell level using oscillating microelectrodes and at the root region level using enriched (15)N application. Our objective was to determine the root regions making the greatest contribution to total N uptake in each species as measured by the two contrasting techniques. White and condensed tannin zones were the regions with the smallest surface area in all species, but these zones often had the highest net flux of NH4(+) and NO3(-). For most species, little variation was found among root regions in N flux calculated using a (15)N mass balance approach, but where significant differences existed, high N flux was observed in white, cork or woody zones. When N fluxes measured by each of the two methods were multiplied by the estimated surface area or biomass of each root region, the effect of root region size had the greatest influence on regional N uptake. Root regions of greatest overall N uptake were the cork and woody zones, on average. Total N uptake may thus be greatest in older regions of tree seedling roots, despite low rates of uptake per unit area.

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.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.016
GPT teacher head0.208
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2014
Admission routes2
Has abstractyes

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