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Record W2239388574 · doi:10.1080/15592324.2015.1117722

Root developmental adaptation to Fe toxicity: Mechanisms and management

2015· article· en· W2239388574 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

VenuePlant Signaling & Behavior · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyAdaptation (eye)Root (linguistics)ToxicityNeuroscienceInternal medicine

Abstract

fetched live from OpenAlex

Iron (Fe) is an essential microelement but is highly toxic when in excess. To cope with Fe excess, plants have evolved complex adaptive responses that include morphological and physiological modifications. The highly dynamic adjustments in overall root system architecture (RSA) determine root plasticity and allow plants to efficiently adapt to environmental constraints. However, the effects of Fe excess on RSA are poorly understood. Recently, we showed that excess Fe treatment in Arabidopsis not only directly impairs primary root (PR) growth but also arrests lateral root (LR) formation by acting at the tip of the growing primary root. Such a change is believed to help RSA adjust and restrict excessive Fe absorption in the part of the rhizosphere subject to acute toxicity while maintaining the absorption of other nutrients in the less stressed components of the root system. We further showed that the suppression of PR growth and LR formation under excess Fe is alleviated by K(+) addition, providing useful insight into the effectiveness of nutrient management to improve RSA and alleviate Fe toxicity symptoms in the field.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.193

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 head0.048
GPT teacher head0.235
Teacher spread0.187 · 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