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Record W6963608555 · doi:10.18739/a2736m29b

Distributed Biological Observatory (DBO) and Conductivity-Temperature-Depth (CTD) data along DBO3 from Canada’s Three Oceans (C3O) project on board the CCGS (Canadian Coast Guard Ship) Sir Wilfrid Laurier, Southern Chukchi Sea, 2014

2014· dataset· en· W6963608555 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2014
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCoast guardObservatoryOn boardData archiveGuard (computer science)

Abstract

fetched live from OpenAlex

This data has been collected and submitted as part of the Distributed Biological Observatory (DBO) program. Data were originally collected as part of the Canada’s Three Oceans (C3O) project. Conductivity-Temperature-Depth (CTD) data were taken aboard the CCGS (Canadian Coast Guard Ship) Sir Wilfrid Laurier. During this cruise, data were taken along the established repeat hydrography transects, DBO3, and DBO4. This submission includes CTD data from the DBO3 transect. There are 8 cnv (Copy Number Variation) data files containing the following parameters: pressure, depth, temperature, conductivity, oxygen, fluorescence, practical salinity, density, and potential temperature.

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)0.003
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 score0.520
Threshold uncertainty score0.954

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.027

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 head0.026
GPT teacher head0.191
Teacher spread0.165 · 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
Published2014
Admission routes1
Has abstractyes

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