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Record W4360806623 · doi:10.1093/jxb/erad110

Open questions in plant cell wall synthesis

2023· article· en· W4360806623 on OpenAlexafffund
Heather E. McFarlane

Bibliographic record

VenueJournal of Experimental Botany · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides and Plant Cell Walls
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCell wallCellGlycanBiologyPolysaccharideEnzymeComputational biologyGlycoproteinBiochemistry

Abstract

fetched live from OpenAlex

Plant cells are surrounded by strong yet flexible polysaccharide-based cell walls that support cells while also allowing growth by cell expansion. Plant cell wall research has advanced tremendously in recent years. Sequenced genomes of model and crop plants have facilitated cataloguing and characterization of many enzymes involved in cell wall synthesis. Structural information has been generated for several important cell wall-synthesizing enzymes. Important tools have been developed including antibodies raised against a variety of cell wall polysaccharides and glycoproteins, collections of enzyme clones and synthetic glycan arrays for characterizing enzymes, herbicides that specifically affect cell wall synthesis, live-cell imaging probes to track cell wall synthesis, and an inducible secondary cell wall synthesis system. Despite these advances, and often because of the new information they provide, many open questions about plant cell wall polysaccharide synthesis persist. This article highlights some of the key questions that remain open, reviews the data supporting different hypotheses that address these questions, and discusses technological developments that may answer these questions in the future.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.008
Scholarly communication0.0050.019
Open science0.0030.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0050.002

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 head0.032
GPT teacher head0.260
Teacher spread0.228 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2023
Admission routes2
Has abstractyes

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