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Record W2158848000 · doi:10.1080/01431160512331314029

A practical approach for estimating the red edge position of plant leaf reflectance

2005· article· en· W2158848000 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Remote Sensing · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsUniversity of CalgaryUniversity of Waterloo
Fundersnot available
KeywordsRed edgeHerbaceous plantRemote sensingReflectivityInversion (geology)Vegetation (pathology)Environmental scienceChlorophyllWavelengthSpectral linePosition (finance)MathematicsBotanyHyperspectral imagingGeologyOpticsBiologyPhysics

Abstract

fetched live from OpenAlex

The point of maximum slope on the reflectance spectrum of a plant leaf between red and near‐infrared wavelengths is known as the red edge position (REP). The REP is strongly correlated with foliar chlorophyll content, and hence it provides a very sensitive indicator for a variety of environmental factors affecting leaves such as stress, drought and senescence. The REP is also present in spectra for vegetation recorded by remote sensing methods. Due to its importance for the application of inversion procedures, a number of techniques have been developed for determining the REP for foliar spectral reflectance. In this paper a new approach is proposed. It allows an unsupervised estimation of the REP. The accuracy of the new approach is evaluated by comparing REP estimates with values derived from measured spectral data for woody and herbaceous species available in the LOPEX (Leaf Optical Properties Experiment) database.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.868
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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