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Thaw front depth at the bottom, on the slopes and on the adjacent tundra polygons of two thermo-erosion gullies on Bylot Island, Nunavut, Canada

2024· dataset· en· W6918144983 on OpenAlexaffabout

Bibliographic record

VenueNordicana D · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité de MontréalCenter for Northern Studies
Fundersnot available
KeywordsTransectFront (military)TundraPolygon (computer graphics)Hydrology (agriculture)Thalweg

Abstract

fetched live from OpenAlex

This dataset presents thaw front depths (TFD) measurements made in two thermo-erosional gullies on Bylot Island, Nunavut, Canada, from probing to refusal with a graduated steel rod. The first gully, TEG1, formed in 1999 and is still active today (2024). The second gully, TEG2, is a gully that has been stabilized for at least 66 years. TFD was measured in 2017 from 13 June to 29 July, and in 2018 from 12 June to 16 August. Measurements were made every 2-3 days along transects of ~30 points (10 to 30 m in length) perpendicular to the TEG and averaged into three positions: 1) shoulder of the gully (the polygon directly adjacent to the gully), 2) gully slope, 3) gully stream.

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 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), Research integrity, Insufficient 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.018
GPT teacher head0.248
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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes2
Has abstractyes

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