In situ observations of juvenile Sea Lampreys in the Gulf of Maine from a noninvasive trawl survey
Bibliographic record
Abstract
ABSTRACT Objective This project aimed to document in situ observations of juvenile Sea Lampreys Petromyzon marinus in the Gulf of Maine using noninvasive optical survey technology and to highlight the potential of this method to help address knowledge gaps in their marine distribution, habitat use, and host associations. Methods From 2019 to 2024, a semi-annual (January and May), stratified random, noninvasive optical trawl survey was conducted in the western Gulf of Maine. Video footage was manually reviewed to identify and record occurrences of Sea Lampreys, their host species, depth, and temperature. Results In total, 46 juvenile Sea Lampreys were observed, 45 of which were attached to fish hosts. Most observations occurred during winter surveys (n = 45). Atlantic Mackerel Scomber scombrus (n = 40) were the most common host, followed by Atlantic Herring Clupea harengus (n = 3), Haddock Melanogrammus aeglefinus (n = 1), and Pollock Pollachius virens (n = 1). Observations were made at depths ranging from 32 to 133 m and at temperatures ranging from 5.1°C to 8.3°C. Conclusions These preliminary in situ observations demonstrate the utility of noninvasive optical surveys for studying the poorly understood marine phase of Sea Lampreys. This technology offers new opportunities to investigate lamprey behavior, habitat preferences, and host interactions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".