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Record W7076160000 · doi:10.5683/sp3/t2wt9m

A climatology of coupled tracks of extratropical cyclones and mesoscale convective systems

2025· dataset· en· W7076160000 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsExtratropical cycloneMesoscale meteorologyMesoscale convective systemSection (typography)ConvectionInterpolation (computer graphics)

Abstract

fetched live from OpenAlex

Data files pertaining to the paper 'A climatology of coupled tracks of extratropical cyclones and mesoscale convective systems.' Submitted to Journal of Geophysical Research: Atmospheres. This dataset aims to combine the two databases from readme section (i) and section (ii) into a single cohesive database of coupled systems. The data itself includes a dataset of mesoscale convective systems (Feng, 2021) and extratropical cyclones (Crawford et al, 2021). Following, we include a dataset of coupled systems in csv format which were developed using an algorithm run between the two datasets. The most intense of these tracks (which were selected based on methods described in the paper) had individual datasets developed via interpolation of ERA5 data, including variables such as temperature, specific humidity, and vorticity, as described in readme section (iv). Related publications, usage, and license included in readme file.

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 score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.022

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 head0.015
GPT teacher head0.303
Teacher spread0.289 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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