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Record W6908376952 · doi:10.26023/nk56-0ccz-cp09

CliC (MAGS): BERMS Meteorological Tower Data Set. Version 1.0

2011· dataset· en· W6908376952 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2011
Typedataset
Languageen
Field
Topic
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsNetCDFData setData fileTowerPeriod (music)Snowpack

Abstract

fetched live from OpenAlex

This data set contains the Coordinated Energy and Water Cycle Observation Project (CEOP) Climate and Cryosphere (CliC; formerly Mackenzie GEWEX [Global Energy and Water Cycle Experiment] Study [MAGS]) Boreal Ecosystem Research and Monitoring Sites (BERMS) Meteorological Tower Data Set. This data set contains 30 minute temperatures, humidities and winds from varying heights from the Old Aspen, Old Black Spruce and Old Jack Pine stations in BERMS for the period 01 October 2002 to 31 December 2009. This data set contains both ASCII data and netCDF data. The ASCII data file covers the entire time period for all stations. The netCDF data file covers the entire time period with one netCDF file for each station.

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)0.003
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 score0.066
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0370.056

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 head0.235
GPT teacher head0.391
Teacher spread0.156 · 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
Published2011
Admission routes1
Has abstractyes

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