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Record W1964477431 · doi:10.3996/032012-jfwm-025

A Simple Method for In Situ Monitoring of Water Temperature in Substrates Used by Spawning Salmonids

2012· article· en· W1964477431 on OpenAlexaboutno aff
Christian E. Zimmerman, James E. Finn

Bibliographic record

VenueJournal of Fish and Wildlife Management · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOncorhynchusSTREAMSEnvironmental scienceHabitatWatershedFisheryFish <Actinopterygii>Hydrology (agriculture)Surface waterEcologyBiologyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Interstitial water temperature within spawning habitats of salmonids may differ from surface-water temperature depending on intragravel flow paths, geomorphic setting, or presence of groundwater. Because survival and developmental timing of salmon are partly controlled by temperature, monitoring temperature within gravels used by spawning salmonids is required to adequately describe the environment experienced by incubating eggs and embryos. Here we describe a simple method of deploying electronic data loggers within gravel substrates with minimal alteration of the natural gravel structure and composition. Using data collected in spawning sites used by summer and fall chum salmon Oncorhynchus keta from two streams within the Yukon River watershed, we compare contrasting thermal regimes to demonstrate the utility of this method.

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 score0.048
Threshold uncertainty score0.320

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 head0.012
GPT teacher head0.259
Teacher spread0.246 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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