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Record W4242578722 · doi:10.1002/wea.2721

In this issue of <i>Weather</i>

2016· article· en· W4242578722 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWeather · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsSnowClimatologyWind speedLapse rateWeather stationCold frontAutomatic weather stationClimate changeWind directionMeteorologyEnvironmental scienceGeologyGeographyPhysical geographyOceanography

Abstract

fetched live from OpenAlex

We begin our February 2016 issue of Weather with a study of the dangers of winds over mountain ranges on p. 27. In ‘Wind hazard in the alpine zone: a case study in Alberta, Canada’ Chris Hugenholtz and Geoffrey Van Heller discuss the effects of winds of a relatively extreme mountain environment using data from an automatic weather station in the Front Ranges of the eastern Rocky Mountains. Dangers may include the buffeting and chilling effects of the wind itself, the melting of snow due to adiabatic warming and the formation of intense areas of low pressure in the lee of the mountains. Economic losses may be significant, and there is a clear need for all to be aware of the effects of strong winds over mountains. On p. 32, the next paper is an interesting study of high‐resolution wind and temperature data recorded at Great Dun Fell on the high ground of the Pennines. Martin Young's article ‘Rapid temperature and wind fluctuations at a mountain site in northern England on 9/10 February 2015’ describes fascinating changes close to the level of a marked temperature inversion at this time last year. The inversion itself descended through the 847m level of this station, the change erratic and involving both rapid wind‐speed and temperature changes over very short periods. Our third paper is a preliminary review of the exceptional and record‐breaking rainfall in Cumbria in December by Stephen Burt, Mark McCarthy, Mike Kendon and Jamie Hannaford. ‘Cumbrian floods, 5/6 December 2015’ is on p. 36. On p. 40, we look at the effects on air quality of three large coal‐fired power stations in Yorkshire, as seen using satellite radiometry. In ‘Detection of the Yorkshire power stations from space: an air quality perspective’ Richard Pope and Miroslav Provod discuss the notable effects of these power stations, seen using 7‐year mean data, the level of pollution rivalling that of Manchester or London. Deciding where a high‐density network of automatic weather stations will give you the best information to plan for severe weather events is a complex matter. A great deal of information is now available for the environment, but it is necessary to bring these data together, as described in the method used in mountainous northern Turkey: ‘A GIS‐based siting technique for automatic weather stations in Trabzon, Turkey’ by Volkan Yildirim, Recep Nisanci, Ebru Husniye Colak and Okan Yildiz on p. 43.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1810.003

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 head0.023
GPT teacher head0.235
Teacher spread0.211 · 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