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Record W1825381239

Collected Data of The Boreal Ecosystem and Atmosphere Study (BOREAS)

2000· article· en· W1825381239 on OpenAlexaboutno aff
Jeffrey A. Newcomer, David Landis, S. Conrad, Shelaine Curd, K. F. Huemmrich, David Knapp, A. Morrell, J. C. Nickerson, Andrea Papagno, D. Rinker

Bibliographic record

VenueNASA Technical Reports Server (NASA) · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBorealTaigaBoreal ecosystemAtmosphere (unit)Climate changeEcosystemEnvironmental scienceSet (abstract data type)Computer scienceASCIIMeteorologyRemote sensingGeographyEcologyForestry
DOInot available

Abstract

fetched live from OpenAlex

The Boreal Ecosystem-Atmosphere Study (BOREAS) was a large-scale international interdisciplinary climate-ecosystem interaction experiment in the northern boreal forests of Canada. Its goal was to improve our understanding of the boreal forests -- how they interact with the atmosphere, how much CO2 they can store, and how climate change will affect them. BOREAS wanted to learn to use satellite data to monitor the forests, and to improve computer simulation and weather models so scientists can anticipate the effects of global change. This BOREAS CD-ROM set is a set of 12 CD-ROMs containing the finalized point data sets and compressed image data from the BOREAS Project. All point data are stored in ASCII text files, and all image and GIS products are stored as binary images, compressed using GZip. Additional descriptions of the various data sets on this CD-ROM are available in other documents in the BOREAS series.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.207
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueNASA Technical Reports Server (NASA)Same topicPeatlands and Wetlands EcologyFrench-language works237,207