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Record W2026685982 · doi:10.1577/a06-013.1

Design of a Portable Streamside Rearing Facility for Lake Sturgeon

2007· article· en· W2026685982 on OpenAlexaboutno aff
J. Marty Holtgren, Stephanie A. Ogren, Aaron J Paquet, Steve Fajfer

Bibliographic record

VenueNorth American Journal of Aquaculture · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceWisconsin Department of Natural Resources
KeywordsBiologySturgeonFisheryZoologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract A portable streamside rearing facility was designed and used by the Little River Band of Ottawa Indians during efforts to rehabilitate a remnant population of lake sturgeon Acipenser fulvescens in the Big Manistee River, Michigan, beginning in 2004. The streamside rearing facility facilitates rearing of wild-caught lake sturgeon larvae in their natal water. This rearing approach provides a cost-effective technique for small batch rearing, incorporates aspects of genetic conservation, and addresses concerns about imprinting and spawning site fidelity. This rearing method may be an important management tool for restoring remnant lake sturgeon populations. Successful rearing of lake sturgeon during the first 3 years of operation indicates that this portable design may be adapted and modified for other locations and fish species. Other management agencies in the Great Lakes basin are currently using this technology for lake sturgeon rehabilitation because of the demonstrated operational success of this facility.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.012
GPT teacher head0.233
Teacher spread0.220 · 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 designBench or experimental
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

Citations45
Published2007
Admission routes1
Has abstractyes

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