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Record W2805916100 · doi:10.4095/293342

Peak season leaf area index for the Nanaimo Aquifer - 2011

2013· report· en· W2805916100 on OpenAlex
M Maloley, Richard Fernandes, Francis Canisius, Christopher R. Butson

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicEnvironmental and biological studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsIndex (typography)AquiferEnvironmental scienceHydrology (agriculture)Leaf area indexForestryGeologyGeographyAgronomyGeotechnical engineeringGroundwaterBiologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This document describes the production and assessment of peak season leaf area index estimates over the Nanaimo Aquifer and surrounding regions from satellite imagery using standard Canada Centre for Remote Sensing algorithms. A 30m resolution map of 2011 peak season leaf area index for the Nanaimo Aquifer was created using a combination of in situ LAI estimates, vegetation indices from remotely sensed spectral data and land cover information from SPOT 5 satellite imagery. A total of 104 ground plots were sampled across the study area between July 15-30, 2011for the purposes of calibration and validation of the leaf area index product.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.375
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0440.004

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 head0.051
GPT teacher head0.248
Teacher spread0.197 · 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

Quick stats

Citations0
Published2013
Admission routes2
Has abstractyes

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