Multibeam Bathymetry, Acoustic Doppler Current Profiler, and Sediment Core Data from the Pointe-des-Monts Underwater Canyon System, St. Lawrence Estuary
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.024 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".