MétaCan
Menu
Back to cohort
Record W2002469668 · doi:10.1080/02755947.2013.824937

Effects of Fixed and Fluctuating Temperature on Hatch of Round Whitefish and Lake Whitefish Eggs

2013· article· en· W2002469668 on OpenAlexafffundabout
Paul H. Patrick, Elaine Chen, Jason C. Parks, Jennifer R. Powell, Joanne Poulton, Cherie‐Lee Fietsch

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsBruce Power (Canada)Ontario Power GenerationSeneca Polytechnic
FundersCANDU Owners GroupBruce PowerMinistry of Natural Resources
KeywordsCoregonus clupeaformisHatchingEgg incubationBiologyCoregonusRange (aeronautics)Animal scienceFish <Actinopterygii>EcologyFisheryEnvironmental scienceZoology

Abstract

fetched live from OpenAlex

Abstract Temperature-response information for use in evaluating thermal discharges is often over 30 years old and in the nonpeer-reviewed literature, especially for Round Whitefish Prosopium cylindraceum and Lake Whitefish Coregonus clupeaformis exposed to nonlethal, elevated, and variable temperatures. Egg incubation experiments on Round Whitefish collected in Lake Ontario and Lake Whitefish collected in Lake Huron were carried out from December 13, 2011, to April 7, 2012. Experimental treatments included ambient baseline control conditions as well as fixed and fluctuating (variable) temperature increases of 1, 2, 3, and 5°C above ambient baseline conditions. For both species, the window for hatching for all experimental temperature treatments was variable (range, 10–38 d for Round Whitefish and 11–44 d for Lake Whitefish), and the hatching windows tended to be greater as temperatures increased. Our results indicated that both fixed and variable incremental increases in temperature above ambient baseline conditions have a statistically significant effect on 50% hatch, and hatch occurs earlier with higher incremental temperature increases. The ecological significance of advanced hatch, such as indirect mortality and food source availability, was evaluated. Received February 19, 2013; accepted July 8, 2013

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.003
GPT teacher head0.180
Teacher spread0.178 · 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

Citations22
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueNorth American Journal of Fisheries ManagementSame topicFish Ecology and Management StudiesFrench-language works237,207