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Record W6910927401 · doi:10.5065/d67942vr

Alexandra Fiord Dry Tundra Ecosystem. Version 1.0

2007· dataset· en· W6910927401 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2007
Typedataset
Languageen
FieldSocial Sciences
TopicHumanities and Social Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsTundraSnowmeltFjordSnowPermafrostAtmosphere (unit)MeltwaterArcticCarbon dioxide

Abstract

fetched live from OpenAlex

The data set presented here represents growing season (late-1999, 2000 and 2001) values of net carbon dioxide exchange, photosynthesis, and respiration between the atmosphere and dry heath tundra. The site is located at Alexandra Fiord on the east-central side of Ellesmere Island, Nunavut, Canada at 78.54N 75.55W, 50 m elevation asl. As part of the International Tundra Experiment (ITEX), Greg Henry of the University of British Columbia has been increasing air and soil temperatures at this site since 1993 using small open-topped chambers (OTCs). These OTCs are hexagonal in shape and are constructed of transparent fiberglass. They typically raise air and soil temperatures by 1 to 4C. The data set shows periodic carbon dioxide exchange data from the end of the 1999 growing season and throughout the 2000 and 2001 growing seasons in ambient plots and long-term (7-9 yrs) warmed (OTC) plots. The most complete data set (2001) begins in spring before winter snowmelt and ends at the end of summer when snow has once again covered the ground. The data are from 199908040800 to 200108042400 UTC.

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)0.002
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.139
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.019

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 head0.075
GPT teacher head0.386
Teacher spread0.310 · 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
GenreDataset

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

Citations0
Published2007
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicHumanities and Social SciencesFrench-language works237,207