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Record W6925179576 · doi:10.17632/t57m65h5hk

Raw data for Ibrahim and Tremblay (2023) Marine Chemistry

2023· dataset· en· W6925179576 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2023
Typedataset
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsRaw dataRaw materialSulfurComposition (language)Data file

Abstract

fetched live from OpenAlex

Raw data for the manuscript submitted to Marine Chemistry in June 2023. Title: Origin of dissolved organic sulfur in marine waters and the impact of abiotic sulfurization on its composition and fate Authors: Hamida Ibrahim and Luc Tremblay Department of Chemistry and Biochemistry, Université de Moncton, Moncton, New Brunswick, Canada E1A 3E9. In the Excel files below, a comma is used to separate the whole and the decimal parts of the numbers. Although the name of these files refers to the Figures and Tables of the manuscript they also contain the data of the Supplementary data file associated with the manuscript.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.008
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.342
Teacher spread0.261 · 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 teacher head, not a consensus.

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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