2019 Framework Assessment of American Lobster (Homarus americanus) in LFA 34–38
Bibliographic record
Abstract
The inshore commercial fishery for American Lobster (Homarus americanus) has been active for over 150 years in Lobster Fishing Areas (LFAs) 34–38. These areas cumulatively cover 34,000 km2 from southwestern Nova Scotia, north to the Bay of Fundy and along the New Brunswick coast to the Canadian—United States border. The fishery is active throughout the LFAs with both inshore and offshore components. Lobster stocks in LFAs 34–38 have a long history of assessments which are conducted almost annually. The last framework for assessing Lobster in LFAs 34–38 occurred in 2013 with separate assessment documents for LFA 34 and LFAs 35–38. The most recent stock assessments for LFA 34 use landings, the Inshore Lobster Trawl Survey (ILTS) catch rate index, and raw commercial catch rates as primary indicators of stock status. LFAs 35–38 were assessed as one unit with a single set of primary stock status indicators. These indicators include landings, raw commercial catch rates, and total abundance from the Fisheries and Oceans Canada (DFO) summer Research Vessel (RV) survey. In this stock assessment framework the stock status indicators were re-examined and their methodologies for estimation evaluated. Background on the available data sources and analyses were described. The code to perform all analyses is available on a GitHub repository. This framework will provide information on ecological and environmental indicators, incrementally moving toward applying an ecosystem approach to stock assessments. Indicators will be estimated for each LFA separately. It was recognized that there are likely connections between LFAs and similar processes impacting production; however, each LFA is managed separately with unique conservation measures adopted. There are three groups of indicators in this document, primary, secondary, and contextual. The primary indicators will be used to define stock status, and reference points will be developed. Secondary indicators are those in which time-series trends will be updated and displayed in subsequent stock status reports; however, no reference points will be developed for these indicators. The contextual indicators will be included in stock assessments, and will be infrequently updated. The data used in this stock assessment represent a mixture of both fisheries dependent and fisheries independent data. The fisheries independent data come from a number of mobile sampling methods. Each of these surveys cover a portion of the overall stock area. The longest time series of data on the Lobster within these LFAs comes from the fisheries dependent data.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".