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Record W2774136920 · doi:10.17957/ijab/15.0345

Influence of Diurnal Temperature Range on the Development of Fiber Cells in Flax (Linum usitatissimum)

2017· article· en· W2774136920 on OpenAlexafffund
Guanghui Du, Liyan Wu, Gang Deng, Yang Yang, Feihu Liu, G. G. Rowland

Bibliographic record

VenueInternational Journal of Agriculture and Biology · 2017
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Saskatchewan
FundersCollege of Agriculture and Bioresources, University of SaskatchewanChina Scholarship Council
KeywordsLinumBiologyDiurnal temperature variationRange (aeronautics)FiberAgronomyBotanyChemistryMaterials science

Abstract

fetched live from OpenAlex

Three flax (Linum usitatissimum L.) cultivars ('Ariane', 'Argos' and 'Viking') were used to study the effect of diurnal temperature range (DIF) applied throughout the whole growth stage on the development of fiber cells. Diurnal temperature ranges were set at 5C, 10C and 15C with the same daily mean temperature and accumulated growing degree days (GDDa). All measured traits showed obvious DIF and varietal differences except the length of fiber bundle (LFB) and the inter-fiber bundle distance (IFBD). Significant interactions of DIF and cultivar were observed to affect the width of fiber bundle (WFB), the size of fiber cell (SFC), the size of fiber cell cavity (SFCC) and the thickness of fiber cell wall (TFCW). Compared with other DIFs, the number of fiber cells per bundle (NFCB) and WFB increased, but IFBD decreased under DIF 5. However, WFB, TFCW and NFCB all decreased under DIF 10. Under DIF 15 condition, both SFC and SFCC increased. For 'Ariane', IFBD was short under DIF 5, but SFC and SFCC were both large under DIF 10. For 'Argos', IFBD was also short under DIF 5. Under DIF 10, WFB, SFC and TFCW were all small, but IFBD was long. For 'Viking', TFCW was small under DIF 10 but large under DIF 15. All these results suggested a definite influence of DIF on the development of fiber cells in flax, and DIF set at 5C benefited the number of fiber cells in a bundle but DIF 15 was optimal for the size of fiber cells.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.123

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 head0.020
GPT teacher head0.279
Teacher spread0.258 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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