Moored Acoustic Doppler Current Profiler (ADCP) and hydrographic measurements from the RAPID WAVE Scotian Line 2008-2014.
Bibliographic record
Abstract
Moored measurements of currents, temperature and salinity made at 6 sites across the Scotian Slope and Rise between October 2008 and September 2014. The measurements were part of the RAPID (Rapid Climate Change) Western Atlantic Variability Experiment (WAVE) funded by the UK Natural Environment Research Council (NERC) and led by the Proudman Oceanographic Laboratory, in partnership with Fisheries and Oceans Canada (DFO) at the Bedford Institute of Oceanography (BIO). The measurement sites were in water depths ranging from 1100m to 3880m near the Halifax Line and its deep-water extension (XHL), where DFO was carrying out hydrographic monitoring which facilitated the field operations and complement the moored datasets. There were 5 deployments of 9-21 months duration at the 6 primary mooring sites between 2008 and 2014. The primary instrumentation at each site and included in this dataset was an upward-looking Acoustic Doppler Current Profiler (ADCP) at 50 m above bottom (mab), and a MicroCat (MC) temperature-salinity sensor at 100 mab, with additional MCs up to 1100m below the surface at the deepest site during the first 4 deployments.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.018 |
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".