Advances in the Ocean Observing System in the Gulf of Maine: Technical capabilities and scientific results
Bibliographic record
Abstract
The Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) includes the University of Maine's comprehensive solar-powered buoy array in the Gulf of Maine. The system serves a wide variety of real-time oceanographic and marine meteorological data and data products to scientists, state and federal regulators, the National Weather Service, the US and Canadian Coast Guards, the National Data Buoy Center, educators, regional natural-resource managers, the Gulf of Maine fishing and maritime industries, local airports and airlines, sailors, and the general public. In addition to the hourly operational data delivery, The University of Maine provides an archive of data and model output that are significantly advancing the scientific understanding of the Gulf of Maine as a physical and ecological system. Over the nearly nine years of operation, the data have revealed marked seasonal and interannual variability of the circulation and physical properties of the Gulf of Maine. A system wide salinity anomaly event that lasted for nearly two years, as well as a potential regime shift in the inflow and outflow transports of the Gulf have been revealed in the data records.
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 | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".