MétaCan
Menu
Back to cohort
Record W4414244125 · doi:10.1080/07055900.2025.2554837

Multi-Level In-Situ Measurements During a Direct Hit by a Significant Tornado

2025· article· en· W4414244125 on OpenAlexaffvenue
David Sills, Connell S. Miller

Bibliographic record

VenueATMOSPHERE-OCEAN · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsTornadoNoise (video)StormTower

Abstract

fetched live from OpenAlex

A rare direct hit by a significant tornado on a weather station is documented, with a peak 1-s wind gust of 53.1 m/s (191.2 km/h) and a surface pressure deficit of 16.0 hPa recorded. Even more uncommon is that the weather station made measurements at four levels (3, 40, 60 and 80 m). For the first time, a low-level tornado wind profile is constructed based on in-situ measurements below 100 m, including peak 1-s wind speeds at three levels at or above 40 m and an estimated peak wind speed at 3 m derived from the surface pressure deficit. This wind profile supports a previously published, mobile radar-based theory that tornado wind speeds generally increase toward ground level, where the vast majority of tornado damage is caused.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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 designObservational
Domainnot available
GenreEmpirical

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 routes2
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicWind and Air Flow StudiesFrench-language works237,207