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Record W6963838201 · doi:10.20383/102.0546

SalishSeaCast hourly surface along-axis wind velocity, temperature and nitrate summary 2015-2019

2022· dataset· en· W6963838201 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

VenueOpen MIND · 2022
Typedataset
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsnot available
Fundersnot available
KeywordsHindcastWind speedSea surface temperatureNitrateWind stressUpwelling

Abstract

fetched live from OpenAlex

Aggregated hourly surface along-axis wind velocity, temperature and nitrate results for 2015-2019 from the SalishSeaCast hourly hindcast archive (https://salishsea.eos.ubc.ca/erddap/). This file is a companion asset to the following publication: B. Moore-Maley and S. E. Allen: Wind-driven upwelling and surface nutrient delivery in a semi-enclosed coastal sea, Ocean Sci., 2022. SalishSeaCast is a NEMO 3.6 configuration for the Salish Sea (https://salishsea-meopar-docs.readthedocs.io/). Along-axis wind velocity and wind stress are calculated from the Environment and Climate Change Canada HRDPS model (https://weather.gc.ca/grib/grib2_HRDPS_HR_e.html). This file has a companion software repository, which includes scripts to recreate the file (https://github.com/SalishSeaCast/SoG_upwelling_EOF_paper).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.213
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1420.002

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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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