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Record W2024724882 · doi:10.1577/m04-053.1

The Use of Two New Portable 12-mm PIT Tag Detectors to Track Small Fish in Shallow Streams

2005· article· en· W2024724882 on OpenAlexafffund
Julien Cucherousset, Jean‐Marc Roussel, Rachel Keeler, Richard A. Cunjak, Roland Stump

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New Brunswick
FundersInstitut National de la Recherche AgronomiqueCanada Research Chairs
KeywordsFish measurementSalmoTransponder (aeronautics)FisheryDetectorTroutSTREAMSJuvenileEnvironmental scienceBrown troutFish <Actinopterygii>HeaderBiologyPhysicsEcologyOpticsComputer science

Abstract

fetched live from OpenAlex

Abstract This paper describes two prototypes of portable detectors based on radio frequency identification modules and antennas commercially available in Europe and North America for reading small (2.1-mm × 11.5-mm) passive integrated transponder tags. Maximum tag detection distances ranged from 17 to 36 cm, depending on the system and orientation of the tag to the antenna. The efficiency of the detectors was field-tested with both wild juvenile brown trout Salmo trutta and adult slimy sculpin Cottus cognatus that had been marked by injection of a tag into the peritoneal cavity. By probing the water with the antenna, we were able to detect, on average, 69% of age-1 trout (fork length, 148 ± 26 mm (mean ± SD)), 82% of age-0 trout (fork length, 72 ± 8 mm), and 82% of adult sculpin (total length, 74 ± 9 mm). We did not conduct a formal study to compare the performances of the two prototypes or to determine how habitat characteristics may alter their efficiency.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.210
Teacher spread0.191 · 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

Citations98
Published2005
Admission routes2
Has abstractyes

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