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Ion uptake in <i>Pinus banksiana</i> treated with sodium chloride and sodium sulphate

2004· article· en· W2018324934 on OpenAlexafffundabout
Jennifer Franklin, Janusz J. Zwiazek

Bibliographic record

VenuePhysiologia Plantarum · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaSyncrude
KeywordsTranspirationSodiumShootChemistrySalinityNutrientChlorideElectrolyteBotanyHorticulturePhotosynthesisBiologyBiochemistry

Abstract

fetched live from OpenAlex

Within its wide range across Canada, jack pine is exposed to salinity from both natural and anthropogenic sources. To compare the effects of Cl and SO(4) on salt injury, sand and solution-culture grown jack pine (Pinus banksiana Lamb.) seedlings were treated with nutrient solutions containing 60 or 120 mM NaCl, 60 mM Na(2)SO(4), or a mixture of 60 mM NaCl and 30 mM Na(2)SO(4). After 5 weeks of salt treatments, concentrations of Cl, K, Na, and SO(4) were determined in roots, stem and needles of the current and previous years growth, and in necrotic needles. To determine the role of water uptake in the absorption and translocation of salts in plants, total transpiration was measured as the loss of water from a sealed system and related to total plant uptake of Cl, Na, and SO(4). Sodium uptake and root-to-shoot transport rates were greater in treatments containing Cl. A delay in root-to-shoot transport of both Na and Cl indicates retention of these ions in the roots. Electrolyte leakage of needles was more closely related to treatment Cl concentrations than treatment Na concentrations. The transport of Na ions to the shoot was related to the presence of Cl, but was not related to transpiration rate.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations55
Published2004
Admission routes3
Has abstractyes

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