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Record W6888359099 · doi:10.18739/a2445hc4r

Canada's Three Oceans (C3O) Shipboard Acoustic Dopper Current Profilers (SADCP) data collected from the Sir Wilfrid Laurier, Southern Chukchi Sea, 2011

2019· dataset· en· W6888359099 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCTDLongitudeCurrent (fluid)CruiseLatitudeCurrent meterFlow (mathematics)

Abstract

fetched live from OpenAlex

This dataset contains includes zooplankton and CTD data from the Sir Wilfrid Laurier cruise during July 2012. Data includes, order, taxonomy, length, and weight. Also included are CTD data from various DBO stations. Data includes unique key, institution, cruise number, ship ID, event #, station name, CTD cast #, project, year, month, day, local time, UTC offset, latitude degrees, latitude minutes, longitude degrees, longitude minutes, flow start, flow end, flowmeter serial, net diameter (m), volume filtered (m3), volMethod_no, net mesh (um), net type, start depth, finish depth, wire out, wire angle, bottom depth (m), and PI.

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)0.005
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 score0.151
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.014
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0370.051

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 head0.043
GPT teacher head0.268
Teacher spread0.224 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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