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Record W6908352642 · doi:10.25923/xcc1-px89

Implementation of the upgraded Lake Ontario Operational Forecast System and Lake Superior Operational Forecast System and the semi-operational nowcast/forecast skill assessment

2023· article· en· W6908352642 on OpenAlexaboutno aff

Bibliographic record

VenueNOAA Institutional Repository · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWater Resources and Governance
Canadian institutionsnot available
FundersNational Ocean ServiceUniversity of Massachusetts DartmouthCenter for Operational Oceanographic Products and ServicesDartmouth CollegeNational Oceanic and Atmospheric AdministrationNOAA Great Lakes Environmental Research LaboratoryU.S. Department of Commerce
KeywordsForecast skillProcess (computing)Training (meteorology)Work (physics)

Abstract

fetched live from OpenAlex

This technical report documents how the NOS CO-OPS builds the control and static files for the High-Performance Computing (HPC) COMF to generate the required model forcing files to drive LOOFS and LSOFS. The nowcast and forecast guidance skill assessment is then presented. As the model’s physics and the setups of LOOFS and LSOFS are the same, the implementation and skill assessments of the two forecast systems are documented in this single technical report.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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