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Record W2098841353 · doi:10.3390/s8010051

Changes in Spectral Properties, Chlorophyll Content and Internal Mesophyll Structure of Senescing Populus balsamifera and Populus tremuloides Leaves

2008· article· en· W2098841353 on OpenAlexaff
K. L. Castro, Arturo Sánchez‐Azofeifa

Bibliographic record

VenueSensors · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChlorophyllChlorophyll aBotanySpongy tissueChlorophyll bChemistryReflectivityHorticultureBiologyOpticsPhysics

Abstract

fetched live from OpenAlex

In this paper we compare leaf traits and spectral reflectance for sunlit andshaded leaves of Populus tremuloides and Populus balsamifera during autumnsenescence using information derived from an Analytical Spectral Devise (ASD) FullRange spectrometer. The modified simple ratio (mSR705) and modified normalizeddifference index (mND705) were effective in describing changes in chlorophyll contentover this period. Highly significant (P less than 0.01) correlation coefficients were found betweenthe chlorophyll indices (mSR705, mND705)) and chlorophyll a, b, total chlorophyll andchlorophyll a/b. Changes in mesophyll structure were better described by the plantsenescence reflectance index (PSRI) than by near-infrared wavebands. Overall, P.balsamifera exhibited lower total chlorophyll and earlier senescence than P. tremuloides.Leaves of P. balsamifera were also thicker, had a higher proportion of intercellular spacein the spongy mesophyll, and higher reflectance at 800 nm. Further research, using largersample sizes over a broader range of sites will extend our understanding of the spectraland temporal dynamics of senescence in P. tremuloides and P. balsamifera and will beparticularly useful if species differences are detectable at the crown level using remotelysensed imagery.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.647

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 head0.021
GPT teacher head0.194
Teacher spread0.173 · 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

Citations104
Published2008
Admission routes1
Has abstractyes

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