MétaCan
Menu
Back to cohort
Record W2281428594

Revised Wind Chill Index (The Development of a New Wind Chill Temperature Chart)

2018· article· en· W2281428594 on OpenAlexaboutno aff
Maurice Bluestein

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2018
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsChartMeteorologyCold weatherNational weather serviceEnvironmental scienceIndex (typography)Warm frontOperations researchComputer scienceEngineeringGeographyMathematicsStatisticsWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

It had been known for many years that the original wind chill temperature charts used by the weather services of Canada and the U.S. were flawed. This speaker applied modern heat transfer principles to the Antarctic research that was the basis for the original charts to demonstrate that the temperatures were much too cold. He then proposed an alternative model that would more accurately depict the effect of wind in cold weather on exposed skin. Media attention and an internet conference sponsored in Canada prompted the U.S. Weather Service to initiate a program to update their charts. This speaker and a Canadian researcher who worked with a similar approach were charged with developing a new chart. An algorithm was completed and the new chart was put into effect in Canada in October and in the U.S. in November, 2001.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.005

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)Same topicWinter Sports Injuries and PerformanceFrench-language works237,207