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Record W7163382767 · doi:10.21966/hz11-3m59

Surface Seawater and Marine Boundary Layer CO2 Observations from the Kwakshua Channel (KC) Buoy on the Central Coast of British Columbia (Research)

2018· dataset· W7163382767 on OpenAlexaboutno aff
Wiley Evans, Katie Campbell, Shawn Hateley, Jessy Barrette

Bibliographic record

VenueHakai Institute · 2018
Typedataset
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBuoySeawaterChannel (broadcasting)Current (fluid)Sea surface temperatureSurface layerBoundary layer

Abstract

fetched live from OpenAlex

Kwakshua Channel, located near Fitz Hugh Sound on the central coast of British Columbia, has been a site for moored, high-resolution measurements of surface seawater and marine boundary layer CO2 content since May 2018. Measurements of in situ temperature, salinity, seawater and atmospheric CO2 partial pressure are made using a Battelle Seaology (MApCO2) System. 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. This data contribution consists of measurements since May 1, 2018.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.199
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.103
GPT teacher head0.292
Teacher spread0.189 · 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
Published2018
Admission routes1
Has abstractyes

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