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Record W7132906225

Stream water temperature and climate change - an ecological perspective

2003· dissertation· W7132906225 on OpenAlexaboutno aff
Yuliya Koycheva

Bibliographic record

VenueTSpace · 2003
Typedissertation
Language
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSTREAMSClimate changeAquatic ecosystemWater qualityHydrology (agriculture)Air temperature
DOInot available

Abstract

fetched live from OpenAlex

Rivers and streams are complex environments where physical, biological and chemical processes take place simultaneously and jointly determine the water quality. Freshwater must be well managed and protected because it shelters an enormous amount of aquatic species. In this context, stream water temperature is a crucial water quality parameter, for it determines the fitness and life of all aquatic organisms. This work reviews the thermal tolerance of such organisms, summarizes their behavioral and physiological responses to temperature, and outlines the major factors determining water temperature. To predict the influence of both air temperature and climate change on streams, Mohseni's non-linear regression model is reviewed and applied to several monitored watersheds in Ontario. A detailed case study involving Wilmot creek shows both the suitability of Mohseni's model for existing temperature regimes, and predicts that an increase of 5°C in air temperature will likely result in an increase in average weekly stream temperatures of between 2.6 and 3.3°C.

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)0.000
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: none
Teacher disagreement score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.294
Teacher spread0.278 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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