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Record W6964912488 · doi:10.25921/v5j2-x847

High-resolution record of surface seawater carbon dioxide (CO2) content collected from Hakai Institute Quadra Island Field Station in Hyacinthe Bay, British Columbia, Canada from 2014-12-19 to 2025-12-18 (NCEI Accession 0208638)

2020· dataset· en· W6964912488 on OpenAlexaboutno aff

Bibliographic record

VenueNational Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) · 2020
Typedataset
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsnot available
Fundersnot available
KeywordsSeawaterBayCarbon dioxideSalinityShoreAccessionSurface water

Abstract

fetched live from OpenAlex

This dataset includes continuous sea surface measurements of partial pressure of carbon dioxide (pCO2), sea surface temperature and salinity collected from Hakai Institute Quadra Island Field Station in Hyacinthe Bay, British Columbia, Canada from 2014-12-19 to 2025-12-18. Quadra Island, at the northern terminus of the Salish Sea, has been a site for shore-based and high-resolution measurement of surface seawater CO2 content since December 2014. Measurements of in situ temperature, salinity, and CO2 partial pressure are made near-continuously on seawater drawn from a sample line with an intake 50 m from shore and a depth of 1 m in Hyacinthe Bay on the eastern side of Quadra Island. The effort to collect these data are part of the Hakai Institute’s directive to advance the understanding of carbon cycling in northeast Pacific coastal settings with specific emphasis on ocean acidification.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.148
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.012

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 head0.014
GPT teacher head0.213
Teacher spread0.198 · 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 designObservational
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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