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Record W6908450484 · doi:10.26071/ogsl-9b07076f-e47b

Time-series Biogenic Matter Export Fluxes Offshore Pointe-des-Monts and Baie-Comeau

2023· dataset· en· W6908450484 on OpenAlexaffabout

Bibliographic record

VenueOGSL repository · 2023
Typedataset
Languageen
FieldSocial Sciences
TopicEvolving Legal Systems and Governance
Canadian institutionsDalhousie UniversityGeological Survey of CanadaUniversité du Québec à RimouskiUniversity of New Brunswick
Fundersnot available
KeywordsSubmarine pipelineParticulatesSediment trapSedimentSubmarine canyonCanyonSubmarineOrganic matterTotal organic carbon

Abstract

fetched live from OpenAlex

This dataset includes measured fluxes of phytoplankton cells, total particulate matter, chloropigments, particulate organic carbon, and particulate nitrogen, as well as carbon and nitrogen isotopic signatures on samples from moored sediment traps deployed offshore Pointe-des-Monts and Baie-Comeau. The sediment trap cups were programmed to rotate approximately every two weeks from November 2020 to September 2021. Offshore Pointe-des-Monts, sinking particles were collected at depths of 154 and 224 m while offshore Baie-Comeau, sinking particles were collected at a depth of 133 m. The objective of this work is to understand the influence of an active submarine canyon system on biogenic matter export fluxes. This project was funded by Réseau Québec Maritime (RQM) and Marine Environmental Observation, Prediction, and Response Network (MEOPAR).

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 score0.700
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.010

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 head0.011
GPT teacher head0.253
Teacher spread0.243 · 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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