More than a century of oceanic hydrography observations reveals profound climate-related changes in the Northwest Atlantic and Eastern Arctic
Bibliographic record
Abstract
Abstract. As part of the new Fisheries Act, Fisheries and Oceans Canada (DFO) has made it a priority to disseminate its data publicly. The project proposed here is to create an open-access data product that includes most of the historical temperature and salinity profiles collected in Atlantic Canada and the Eastern Arctic. This project does not aim to replace a potential database, but rather provides an easily accessible and quality-controlled product that can inform fisheries management and support DFO priorities such as the Ecosystem Approach to Fisheries Management, Marine Spatial Planning and the Blue Economy. The Canadian Atlantic Shelf Temperature-Salinity (CASTS) data product consists of 853,748 individual casts [as of 2025-08-22] collected in a geographical zone corresponding to [35–80° N] and [42–100° W] since 1873. The data sources used to make this product were gathered from multiple sources, including DFO regional archives at the Maurice-Lamontagne Institute (MLI), the Bedford Institute of Oceanography (BIO), and the Northwest Atlantic Fisheries Center (NAFC). Other sources of data include the Marine Institute of Memorial University of Newfoundland, data from international ships of opportunity archived by the Marine Environmental Data Services (MEDS), and the Polar Data Catalog. This data product also offers new opportunities to review the changes in the ocean climate of Atlantic Canada, another priority of the Government of Canada. The analysis of these data collected over more than a century also reveals the profound changes undergone by the Northwest (NW) Atlantic Ocean during that period. Climate highlights include large decadal fluctuations of temperature and salinity throughout the entire zone, as well as sustained warming trends on the Scotian Shelf and the Bay of Fundy since the early 1990s, coinciding with an important freshening on the Newfoundland and Labrador (NL) Shelf during the same period. The CASTS data product is available at https://doi.org/10.20383/103.01191 (Coyne et al., 2023).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".