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Record W2184784556

Testing Foliar Absorption in Black Spruce (Picea mariana (Mill.) BSP) Saplings

2014· article· en· W2184784556 on OpenAlexaff
Evelyn Beliën, Sergio Rossi, Hubert Morin, Annie Deslauriers, Joseph Gaudard

Bibliographic record

VenueConstellation (Université du Québec à Chicoutimi) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsBlack sprucePhotosynthesisCanopyAbsorption of waterIrrigationAbsorption (acoustics)BotanyEnvironmental scienceHorticultureAgronomyBiologyTaigaEcologyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Foliar absorption is a known water acquisition mechanism in many species and ecosystems. Experiments in the field showed that mature black spruce [Picea mariana (Mill.) BSP] can surprisingly sustain periods of summer drought. A possible explanation for this phenomenon is that this species is able to rehydrate via its needles. In this study, we explored if black spruce saplings are able to absorb water via the needles or to increase their water potential and photosynthesis after needle wetting. Forty saplings were used, of which half were excluded from irrigation until water potential of -2.70 MPa. For the first part of the experiment, the saplings were sprayed at night with a colorant solution and water potential was measured the following day. No colorant was absorbed by the saplings and no difference in water potential was found between irrigated and non-irrigated individuals. The experiment was then repeated, spraying saplings with normal water and measuring water potential and photosynthesis. Once again there was no increase in water potential or photosynthesis following the canopy spraying. The results of this study show no evidence of foliar absorption in black spruce saplings. However this does not exclude the occurrence of foliar absorption via passive or active mechanisms in mature trees, which grow under different circumstances.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.998

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)0.0050.000

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 head0.007
GPT teacher head0.163
Teacher spread0.156 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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