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Record W6924999019 · doi:10.1594/pangaea.962871

Soil moisture and temperature at Trail Valley Creek, NWT, Canada, in 2019

2023· dataset· en· W6924999019 on OpenAlexaboutno aff

Bibliographic record

VenuePublishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research) · 2023
Typedataset
Languageen
FieldHealth Professions
TopicMethodologies in Health Research and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostWater contentTundraSoil waterHydrology (agriculture)Active layerMoistureArcticAutomatic weather station

Abstract

fetched live from OpenAlex

This data set contains quality controlled soil temperature and volumetric liquid water content measurements from a site at the forest-tundra transition in the western Canadian Arctic. The measurement site is near by the Trail Valley Creek (TVC) research station, which is operated by Wilfried Laurier University. The station is located east of the Mackenzie Delta and 45 km north of Inuvik. The published data set provides long-term observations on the thermal and hydrological state of the active layer at a hummocky tundra site within the continuous permafrost zone. The station consists of a soil depth-profile with four sensor sets at 2cm, 5cm, 10cm, and 20cm of paired soil moisture and soil temperature sensors. Additionally, three distributed soil moisture sensors are installed in the surface soil. The data series is continued since 2016 and provides a basis for process understanding and modelling studies of Arctic permafrost.

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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.012
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.014

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 head0.209
GPT teacher head0.422
Teacher spread0.213 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePublishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)Same topicMethodologies in Health Research and PracticeFrench-language works237,207