DRAFT ENVIRONMENTAL IMPACT STATEMENT- INITIAL REGULATORY IMPACT REVIEW- INITIAL REGULATORY FLEXIBILITY ANALYSIS For Proposed Effort Control Measures For the American Lobster Fishery FEDERAL AMERICAN LOBSTER MANAGEMENT in the Exclusive Economic Zone based
Bibliographic record
Abstract
your review the Draft Environmental Impact Statement (DEIS) for Proposed Effort Control Measures for the American Lobster Fishery. This DEIS is prepared pursuant to NEPA to assess the environmental impacts associated with NOAA's National Marine Fisheries Service (NMFS) proceeding with proposed alternatives to establish limited access programs using historical participation to control fishing effort in the lobster trap fishery in the nearshore waters from Cape Cod, Massachusetts to New York, comprising lobster Management Area 2 and the Outer Cape Area. Lobstermen fishing with traps in Area 2, the Outer Cape Area, and Area 3, the offshore Area from the u.S./Canada border to North Carolina, would be allowed to transfer (buy and/or sell) blocks of lobster traps to other lobstermen. With each transfer of traps, a percentage of the total traps transferred would be permanently eliminated as a resource conservation tax. Additional copies of the DEIS may be obtained from the Responsible Program Official identified below. The document is also accessible electronically through the NMFS Northeast Region's website at:
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 | 0.028 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.013 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.023 |
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".