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Record W6962813052 · doi:10.17882/97660

Sedimentary cores CAS16-03PC and CAS16-14PC dataset from CASEIS Cruise

2023· dataset· en· W6962813052 on OpenAlexaffabout

Bibliographic record

VenueSEANOE · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsCoringSedimentary rockStratigraphyGrabenCruiseCore sampleCore (optical fiber)Sedimentary basin

Abstract

fetched live from OpenAlex

This dataset contains the data acquired on the sedimentary cores collected with the Calypso piston coring system at the same location (17°05.212’N, 60°50.248’W, 5821 mbsl) in the Falmouth Half Graben offshore the Guadeloupe island (Lesser Antilles) during the research cruise CASEIS (DOI 10.17600/16001800) on board of the R/V Pourquoi Pas?, between May 28th to July 05th 2016. Two cores were sampled in this basin the CAS16-03PC and CAS16-14PC cores, which are 9.50 and 26.50 m-long, respectively. This dataset consists of the photo took on the core CAS16-03PC and the raw data measured on the longest core, the core CAS16-14PC: 1) on board with the GEOTECK Multi Sensor Core Logger of the Quebec University at Rimouski (on the whole core: P-wave velocity, gamma density, and volumetric magnetic susceptibility; and on the split core: high resolution photographs, surface magnetic susceptibility and spectrophotocolorimetry); and 2) the X-ray images with the GEOTEK X-ray CT and the semi-quantitative chemical elementary profiles with an AVAATECH XRF core scanner at IFREMER. The stratigraphy of both cores appears identical. The core CAS16-14PC records 29 turbidites, including 4 thicker sedimentary event (up to 5 m-thick), intercalated with hemipelagic sediment layers.

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)0.002
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 score0.187
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.016

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 head0.034
GPT teacher head0.306
Teacher spread0.271 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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