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Record W266405260

BOREAS TE-9 PAR and Leaf Nitrogen Data for NSA Species

2000· article· fr· W266405260 on OpenAlex
Forrest G. Hall, Shelaine Curd, Qing‐Lai Dang, Hank A. Margolis, Marie R. Coyea

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

VenueNASA Technical Reports Server (NASA) · 2000
Typearticle
Languagefr
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité LavalLakehead University
Fundersnot available
KeywordsPhotosynthetically active radiationBorealEnvironmental scienceTaigaForestryEcoregionOak Ridge National LaboratoryGeographyEcologyBlack spruceBiologyBotanyPhotosynthesis
DOInot available

Abstract

fetched live from OpenAlex

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-9 (Terrestrial Ecology) team collected several data sets related to chemical and photosynthetic properties of leaves in boreal forest tree species. This data set describes the relationship between photosynthetically active radiation (PAR) levels and foliage nitrogen in samples from six sites in the BOREAS Northern Study Area (NSA) collected during the three 1994 intensive field campaigns (IFCs). This information is useful for modeling the vertical distribution of carbon fixation for these different forest types in the boreal forest. The data were collected to quantify the relationship between PAR and leaf nitrogen of black spruce, jack pine, and aspen. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.244
Teacher spread0.221 · 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