GoMA GOOS: A GOOS Pilot Project in the Gulf of Maine Region
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.A GOOS pilot project in the Gulf of Maine region has been initiated by Fisheries and Oceans Canada and the US National Marine Fisheries Service. The overarching goal of the project is to develop the necessary capabilities and procedures for utilizing the Integrated Ocean Observing System (IOOS) in support of the conservation objectives for an Ecosystem Approach to Fishery Management (EAFM). To that end activities are underway in three areas. The first is identifying the decision requirements for conservation strategies of EAFM and the pertinent indicators that could be derived from ocean observations to support those decisions. The second is working with other ocean data collecting partners to implement the infrastructure for a Gulf of Maine regional IOOS so that the various, relevant data sets can be easily accessed and integrated for analysis. The third activity is initiating directed research efforts to improve the oceanographic and ecological forecast model capabilities in the region. The GoMA GOOS pilot project is scheduled to be conducted over a 5-year period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".