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Record W4414062463 · doi:10.1093/mcfafs/vtaf028

In situ observations of juvenile Sea Lampreys in the Gulf of Maine from a noninvasive trawl survey

2025· article· en· W4414062463 on OpenAlexaff
Nicholas M. Calabrese, Stephanie L Merhoff, Helena L Norton, Kevin D. E. Stokesbury

Bibliographic record

VenueMarine and Coastal Fisheries · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsBedford Institute of Oceanography
FundersCommonwealth of MassachusettsNorth Carolina Division of Marine Fisheries
KeywordsClupeaPetromyzonHaddockScomberAtlantic herringJuvenileHerringMackerelLampreyPollock

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.213
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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