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Record W2323343077 · doi:10.1093/treephys/25.8.993

A unified nomenclature for quantification and description of water conducting properties of sapwood xylem based on Darcy's law

2005· article· en· W2323343077 on OpenAlexafffund
Douglas E.B. Reid, U. Silins, C. A. Mendoza, Victor J. Lieffers

Bibliographic record

VenueTree Physiology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNomenclatureTerminologyXylemDarcy's lawCLARITYComputer scienceLawMathematicsChemistryPorous mediumBotanyLinguisticsBiologyTaxonomy (biology)PhilosophyPolitical science

Abstract

fetched live from OpenAlex

The literature dealing with the water conducting properties of sapwood xylem in trees is inconsistent in terminology, symbols and units. This has resulted from confusion in the use of either an analogy to Ohm's law or Darcy's law as the basis for nomenclature. Ohm's law describes movement of electricity through a conductor, whereas Darcy's law describes movement of a fluid (liquid or gas) through a porous medium. However, it is generally not realized that, in their full notation, these laws are mathematically equivalent. Despite this, plant physiologists have failed to agree on a convention for nomenclature. As a result, the study of water movement through sapwood xylem is confusing, especially for scientists entering the field. To improve clarity, we suggest the adoption of a single nomenclature that can be used by all plant physiologists when describing water movement in xylem. Darcy's law is an explicit hydraulic relationship and the basis for established theories that describe three-dimensional saturated and unsaturated flow in porous media. We suggest, therefore, that Darcy's law is the more appropriate theoretical framework on which to base nomenclature describing sapwood hydraulics. Our proposed nomenclature is summarized in a table that describes conventional terms, with their formulae, dimensions, units and symbols; the table also lists the many synonyms found in recent literature that describe the same concepts. Adoption of this proposal will require some changes in the use of terminology, but a common rigorous nomenclature is needed for efficient and clear communication among scientists.

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 score0.172
Threshold uncertainty score0.160

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 head0.047
GPT teacher head0.223
Teacher spread0.176 · 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

Citations38
Published2005
Admission routes2
Has abstractyes

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