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Record W2900502279 · doi:10.1594/pangaea.888566

Multisensor ground-based measurements of the permafrost thaw subsidence in the Trail Valley Creek, NWT, Canada, 2015-2016

2018· dataset· en· W2900502279 on OpenAlexaboutno aff
Katharina Anders, Sofia Antonova, Inga Beck, Julia Boike, Bernhard Höfle, Moritz Langer, Philip Marsh, Sabrina Marx

Bibliographic record

VenueFigshare · 2018
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostGeologyGround subsidenceSubsidenceArchaeologyPhysical geographyGeomorphologyHydrology (agriculture)GeographyGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

The datasets were acquired at the Arctic tundra site of Trail Valley Creek (TVC), Northwest Territories, Canada, which is underlain by continuous permafrost. With the objective to quantify thaw/freeze dynamics of the ground over time, the two study sites (about 50x50 m each) were repeatedly captured in June 2015, August 2015, and August 2016 by terrestrial laser scanning (TLS) and by Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) measurements. Additionally, 24 fiberglass poles were anchored deep in the permafrost and, therefore, assumed to be motionless. With these poles, surface displacement was estimated by measuring repeatedly the distance between ground surface and the top of the poles in June 2015, August 2015, July 2016, August 2016 and June 2017. Furthermore, thaw depths were measured around each fiberglass pole. Additionally, one-time GNSS measurements of the ground surface elevation were acquired at a number of points outside of the two study sites.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4770.001

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 head0.110
GPT teacher head0.268
Teacher spread0.157 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

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