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Record W1497569944 · doi:10.1002/met.1404

A new index for the verification of accuracy and timeliness of weather warnings

2013· article· en· W1497569944 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMeteorological Applications · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsWave Control Systems (Canada)Environment and Climate Change Canada
Fundersnot available
KeywordsIndex (typography)Computer scienceWarning systemSet (abstract data type)MeteorologyData miningGeographyTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT A new scoring index is proposed for the verification of the C anadian weather warning program. Called weather warning index ( WWI ), the new measure is designed to be sensitive to two attributes of warnings, their timeliness and accuracy, and to summarize the verification information into a single value for a representative set of regions of C anada and for several weather elements for which warnings are issued. Given the opposing nature of the two attributes (long lead times are likely to be associated with lower accuracy), it was necessary to carefully balance the score to keep it proper in a general sense. The design decisions for the WWI are presented and discussed, and the score computation is illustrated with sensitivity experiments using 3 years of warning forecasts and observations. Copyright © 2013 Royal Meteorological Society

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score0.999

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)0.0020.000

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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