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Record W2740591417 · doi:10.4095/219917

LAI Measurements in White Beans and Corn Canopies with Two Optical Instruments

2001· report· en· W2740591417 on OpenAlexaffabout
A. Pacheco, A. Bannari, K. Staenz, Heather McNairn

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsWhite (mutation)GeographyEnvironmental scienceForestryAgronomyRemote sensingMathematicsBiology

Abstract

fetched live from OpenAlex

Leaf Area Index (LAI) is a parameter used to describe the percentage of vegetation cover and to estimate productivity or yield of agriculture and forest canopies. LAI can be estimated using different techniques such as destructive sampling, vegetation indices and optical instruments. This paper investigates LAI measurements in white beans and corn canopies using two optical instruments, the LI-COR LAI-2000 and the Tracing Radiation and Architecture of Canopies (TRAC), a prototype instrument designed by the Canada Centre for Remote Sensing (CCRS). LAI estimates provided by each instrument are compared and analysed. Also, further investigation is done in regards to the percent crop cover data and LAI values from the LAI-2000 and the TRAC. Preliminary results indicate that LAI measurements with the LAI-2000 and the TRAC do not correlate very well. It was also found that LAI-2000's LAI estimates correlate better with the percent crop cover than the TRAC. Accordingly, the LAI-2000 provides LAI values that are more accurate than those provided with the TRAC.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.677
Threshold uncertainty score0.992

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 head0.032
GPT teacher head0.259
Teacher spread0.227 · 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

Citations8
Published2001
Admission routes2
Has abstractyes

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