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Record W3000717895 · doi:10.1111/nph.16384

An introduction to a Virtual Issue on Wood Biology

2020· editorial· en· W3000717895 on OpenAlexaff
Andrew Groover, Shawn D. Mansfield

Bibliographic record

VenueNew Phytologist · 2020
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of British Columbia
FundersU.S. Forest ServiceU.S. Department of Agriculture
KeywordsLibrary scienceArchaeologyHistoryComputer science

Abstract

fetched live from OpenAlex

An introduction to a Virtual Issue on Wood BiologyThis Virtual Issue 'The biology of wood', highlights the central role of wood biology in basic plant science, as well as critical ecological, environmental, economic and societal issues.Wood, or secondary xylem, is produced by the vascular cambium and plays myriad interacting roles in plant development, physiology and biochemistry.Wood is not simply the terminal product of secondary cell wall development in specialized cells, but is the tissue which enables water conduction and provides structural support for the production of complex plant bodies including massive forest trees.Additionally, woody tissues participate in specialized biochemistry, and store and mobilize nutrients and carbohydrates, in addition to the water vital to survival.Recent research on wood biology has been driven, in part, by the economic value of wood for forest industries and, more recently, bioenergy applications.However, the increasing pressure on forests by anthropogenic climate change and its related episodic heat and drought is driving a need to understand how water transport in tree stems relates to water stress.The papers in this collection are associated with a New Phytologist symposium 'The biology of wood: from cell to trees' that was held in Lake Tahoe, California, in July 2018 (42 nd New Phytologist Symposium https://www.newphytologist.org/symposia/42).The symposium stressed a need for integrative research that addresses how development, cell differentiation, genetics, physiology, and evolution intersect and contribute to the requirements of a comprehensive understanding of wood biology (Mizrachi, 2019).A fascinating aspect of wood biology is the dynamic interplay among environmental cues, development, and physiology.For example, wood development is highly responsive to environmental conditionsas illustrated in angiosperm trees that modify wood development in response to water stressto create newly formed wood that is more resistant to water stress-induced cavitation and mortality (Rodriguez-Zaccaro & Groover, 2019).Elucidating how environmental signals are perceived and translated into changes in development, and how these changes in development interplay with system-level tree physiology, are current examples of critical research areas that require cross-disciplinary approaches which have historically been underrepresented in this field.As outlined below, the papers within this collection illustrate the growing integration of wood biology research across disciplines, and highlight opportunities for new research that will undoubtedly provide new insights and applications for practical issues including forest utilization and responses to climate change, as well as basic insights into the evolution, development, and physiology of forest trees.

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)0.002
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.168
Threshold uncertainty score0.561

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0080.008
Open science0.0020.004
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.1680.095

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 head0.009
GPT teacher head0.273
Teacher spread0.263 · 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
GenreEditorial

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

Citations2
Published2020
Admission routes1
Has abstractyes

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