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Record W6969021746 · doi:10.5683/sp2/jtiqdo

Four Component Radiation Data at Scotty Creek, NWT, Canada 2004-2019

2021· dataset· en· W6969021746 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPermafrostPlateau (mathematics)Land coverWetlandHydrology (agriculture)Instrumentation (computer programming)EvapotranspirationCover (algebra)

Abstract

fetched live from OpenAlex

This dataset includes data for the manuscript entitled, "Long-term climate-influenced land cover change in discontinuous permafrost peatland complexes”. This study combines extensive geomatics data with ground-based meteorological and hydrological measurements to inform a new conceptual model of landscape evolution that accounts for the observed patterns of permafrost thaw-induced landcover change, and provides a basis for predicting future changes. Included here are four component radiation data from four sites, each representing a stage of landscape evolution. Specifically, incoming shortwave, outgoing shortwave, incoming longwave, and outgoing longwave radiation were measured (W/m2) at 30-minute intervals beginning as early as 2004 and continuing through 2019. The four sites instrumented and included in this dataset are: a densely forested plateau site (2007-2019), a sparsely forested plateau site (2015-2018), an intermediate forested plateau site (2014-2019), and a wetland site with no forest cover (2004-2019). Details of instrumentation are included in the aforementioned manuscript.

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)0.000
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.028
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.010
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.014

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 head0.040
GPT teacher head0.268
Teacher spread0.228 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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