MétaCan
Menu
Back to cohort
Record W3107042669 · doi:10.22621/cfn.v134i3.2437

Freshwater turtle by-catch from angling in New Brunswick, Canada

2020· article· en· W3107042669 on OpenAlexafffundvenueabout
Constance L. Browne, Sian Sullivan, Donald F. McAlpine

Bibliographic record

VenueThe Canadian Field-Naturalist · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsUniversity of New Brunswick
FundersFonds en Fiducie pour la Faune du Nouveau-Brunswick
KeywordsTurtle (robot)ChelydraPainted turtleFishingRecreationFisheryThreatened speciesGeographyBycatchRecreational fishingPopulationCatch and releaseEcologyBiologyDemographyHabitat

Abstract

fetched live from OpenAlex

Turtles are among the most threatened vertebrate taxa, with populations especially vulnerable to any increase in adult mortality. By-catch from freshwater angling, as a potential cause of turtle mortality is poorly documented and little understood. Here we document cases of turtle by-catch by recreational anglers in an urban park in New Brunswick and among the wider angling communities in the province. We also consider factors that may influence rates of hooking. Although we are unable to estimate turtle hooking frequency for the provincial recreational angling community as a whole, five of 75 (~7%) anglers interviewed in the urban park reported interactions with a turtle, with most reported incidents (75%) involving hooking. Snapping Turtles (Chelydra serpentina) seem to be more prone to hooking than Eastern Painted Turtles (Chrysemys picta picta). Although we conclude that turtle hooking by recreational anglers appears to be generally uncommon in New Brunswick, even apparently low by-catch rates may be sufficient to lead to population declines at heavily fished sites. The collection of additional data on turtle by-catch in the recreational fishery in Canada is warranted.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.188
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2020
Admission routes4
Has abstractyes

Explore more

Same venueThe Canadian Field-NaturalistSame topicTurtle Biology and ConservationFrench-language works237,207