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Record W6908349885 · doi:10.25850/nioz/7b.b.uf

Underway surface seawater high-resolution pH time series for R/V Sonne cruise SO289.

2023· dataset· en· W6908349885 on OpenAlexaff

Bibliographic record

VenueData Portal of the Royal Netherlands Institute for Sea Research · 2023
Typedataset
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGeotracesAlkalinitySonneCruiseSeawaterBuoyCarbonate

Abstract

fetched live from OpenAlex

This dataset contains a high-resolution (1 measurement every 30 seconds) time series of surface ocean pH in the South Pacific Ocean measured with a PyroScience fiber-based pH sensor (PHROBSC-PK8T) and cross-calibrated using discrete carbonate system observations (total alkalinity and dissolved inorganic carbon). The measurements were collected during R/V Sonne cruise SO289 in February-April 2022,as part of the GEOTRACES GP21 research programme to build an understanding of the distribution, origins, and depletions of trace elements and their isotopes (TEIs) in a lesser-explored ocean region. Bad results from technical issues during analysis have been removed from these results, so there are no recognised issues. The NIOZ created the metadata entry and is responsible for holding master copies of the data.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.038

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 head0.130
GPT teacher head0.329
Teacher spread0.199 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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