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Record W2006227972 · doi:10.1139/x01-158

Water relations, cuticular transpiration, and bud characteristics of air-slit containerized<i>Picea glauca</i>seedlings in response to controlled irrigation regimes

2001· article· en· W2006227972 on OpenAlexvenueno aff
Debra C. Stowe, Mohammed S. Lamhamedi, Hank A. Margolis

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsnot available
Fundersnot available
KeywordsSeedlingTranspirationHorticulturePrimordiumShootIrrigationGrowing seasonBotanyBiologyAgronomyPhotosynthesis

Abstract

fetched live from OpenAlex

White spruce seedlings (Picea glauca (Moench) Voss) were grown in air-slit containers (IPL 25-350A) in a tunnel under four different irrigation regimes (IR-15%, IR-30%, IR-45%, and IR-60%, v/v; (cm H 2 O) 3 ·(cm substrate) –3 ). At the end of the first growing season the water-relation variables of the shoots were determined. Seedling morphology, the rates of cuticular transpiration and terminal bud development, as well as the number of needle primordia were also measured. Irrigation regime had no significant effect on any of the water-relation variables. Seedlings grown under the IR-15% were smaller and completed bud development more quickly than seedlings grown under IR-30%, IR-45%, and IR-60%. The formation of needle primordia was enhanced under IR-30%. Both the irrigation regime and the amount of time the detached shoots were left to transpire had a significant effect on the rate of cuticular transpiration. A comparison of the water-relation variables at the end of the first (1998) and second (1999) growing seasons showed that the younger seedlings had more negative osmotic potential at tissue saturation and greater maximum modulus of elasticity values. None of the other water-relation variables were significantly affected by seedling age, but the absolute values of all the variables were greater in the younger (1+0) seedlings.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.033
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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 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

Citations18
Published2001
Admission routes1
Has abstractyes

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