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Record W7114990092 · doi:10.26071/7bb5f2d7-b91e-46ce

Multibeam Bathymetry, Acoustic Doppler Current Profiler, and Sediment Core Data from the Pointe-des-Monts Underwater Canyon System, St. Lawrence Estuary

2025· dataset· en· W7114990092 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOGSL repository · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité LavalUniversity of New BrunswickGeological Survey of Canada
Fundersnot available
KeywordsBathymetryCanyonSubmarine canyonSubmarine pipelineCurrent (fluid)Turbidity currentEstuaryAcoustic Doppler current profilerSubmarine

Abstract

fetched live from OpenAlex

This dataset includes multibeam bathymetric maps, time-evolution bathymetric profiles of submarine canyon slopes calculated from 3 different bathymetric maps (2015, 2020 and, 2022), downward Acoustic Doppler Current Profiler and CTD time series from October 2020 to Oct 2022, CTD profiles around Pointe-des-Monts, high resolution photography, radiography and laminography of short sediment cores, and magnetic susceptibility, D50 and sorting along each sediment core sampled offshore Pointe-des-Monts. The objective of this work is to determine the recurrence of turbidites observed in the short sediment cores in order to determine if they reflect turbidity current activity within the Pointe-des-Monts submarine canyon system. The second objective is to determine the influence of bottom currents on the sedimentary deposits record. This project was originally 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.

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 categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.005
Research integrity0.0010.002
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 head0.045
GPT teacher head0.302
Teacher spread0.257 · 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

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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