MétaCan
Menu
Back to cohort
Record W7100318193

Evaluation of a Topless Bottom Trawl Design with a 160 foot Headrope and Two Restrictor Lines for Fish Capture in the Summer Flounder Fishery

2014· article· en· W7100318193 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsFlounderFishingFish <Actinopterygii>BycatchFoot (prosody)Sea turtle
DOInot available

Abstract

fetched live from OpenAlex

contained herein.&amp;quot; 1 Previous conservation engineering experiments using a turtle excluder device (TED) in the summer flounder fishery resulted in a significant loss of target species, about 35 % on average. The evaluation of a 106-foot headrope topless trawl in the summer flounder fisheries had no significant loss of target species, but was ineffective at reducing sea turtle bycatch. A 160-foot headrope was effective at reducing sea turtle catch, but was then tested in the summer flounder fishery for target catch retention and had a significant loss of target species, ranging from 51-74 % on average. In an effort to reduce catch loss, this 160-foot headrope net was evaluated at the flume tank at the Marine Institute in St. John’s, Newfoundland and was reconfigured with two restrictor lines. The 160-foot topless trawl with 30 floats and two restrictor lines was tested in the summer flounder fishery in the summer of 2013 to assess its ability to catch finish. The purpose of this report is to present the methodology used, data collected, and a basic analysis on the catch efficiency of the 160 foot headrope topless trawl design compared to a traditional trawl design. The results of this evaluation show that the 160 foot headrope topless trawl with restrictor lines significantly reduced the catch of summer flounder but with the proper float arrangement, the loss of target species was reduced to a 22.7 % loss when compared to a traditional trawl.

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)0.001
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 score0.028
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.063
GPT teacher head0.279
Teacher spread0.216 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicTurtle Biology and ConservationFrench-language works237,207