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Record W2121713868 · doi:10.1017/s026646740700421x

Visual assessment of wilting as a measure of leaf water potential and seedling drought survival

2007· article· en· W2121713868 on OpenAlexaff
Bettina M. J. Engelbrecht, Melvin T. Tyree, Thomas A. Kursar

Bibliographic record

VenueJournal of Tropical Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Alberta
FundersAndrew W. Mellon Foundation
KeywordsBiomeEnvironmental scienceWater contentSeedlingWiltingHabitatEcosystemRange (aeronautics)AgroforestryAgronomyEcologyBiology

Abstract

fetched live from OpenAlex

Rainfall and soil moisture availability vary greatly both spatially and temporally. They are prime factors influencing species distribution patterns, diversity and habitat associations in a range of biomes, and limit primary productivity in many natural ecosystems, as well as in forestry and agricultural systems (Hawkins et al. 2003, Kozlowski & Pallardy 1997, Lieth 1975). Projections of drying trends, and increased frequency and intensity of drought events with climate and land-use changes (Hulme & Viner 1998, IPCC 2001) have fuelled an increased interest in the role of drought in determining the structure and function of natural and managed forest systems (Allen & Breshears 1998, Miles et al. 2004). Such projections accentuate the need to assess, understand and predict plant reactions to drought, as well as soil moisture variation at different scales.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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 designObservational
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

Citations69
Published2007
Admission routes1
Has abstractyes

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