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Record W6908364139 · doi:10.26023/w1s2-zed1-ap0n

Lake-ICE: High Resolution Research Soundings from Algonquin. Version 1.0

2011· dataset· en· W6908364139 on OpenAlexaboutno aff

Bibliographic record

VenueEarth Observing Laboratory · 2011
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDepth soundingAtmospheric soundingHigh resolutionData setQuality (philosophy)Data quality

Abstract

fetched live from OpenAlex

This data set contains ten second vertical resolution sounding data for Algonquin Park, Ontario Canada. This site was operated by the Atmospheric Technology Division(ATD). Soundings were typically taken either four times a day or eight times a day during IOPs,i.e. every three or six hours beginning with 00 UTC. This dataset underwent JOSS automatic quality control procedures. Since the soundings are loaded into the database by actual release times and the actual hour of release is typically one hour before the nominal time, when attempting to preview a sounding try the hour right before the nominal time first. For example: for an 18 UTC sounding, try using hour 17. Consult the README for more information.

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)0.002
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 score0.479
Threshold uncertainty score0.964

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.025

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 head0.073
GPT teacher head0.313
Teacher spread0.240 · 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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