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Record W2884873261 · doi:10.1080/14634988.2018.1500059

Water circulation in Toronto Harbour

2018· article· en· W2884873261 on OpenAlexafffundabout
Bogdan Hlevca, Mathew G. Wells, Liset Cruz‐Font, Susan E. Doka, Rick Portiss, Meg St. John, Steven J. Cooke

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton UniversityFisheries and Oceans CanadaMinistry of EnvironmentToronto and Region Conservation AuthorityThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsOceanographyUpwellingHarbourFlushingEnvironmental scienceContext (archaeology)SeicheWater qualityCurrent (fluid)Hydrology (agriculture)GeologyEcology

Abstract

fetched live from OpenAlex

We present an overview of physical processes that drive water circulation within the extended system of coastal embayments in the Toronto Harbour. The different water circulation patterns occur at various spatial and temporal scales, and our article provides context for the various efforts to improve water quality by the Toronto and Region Remedial Action Plan. Velocity profiles and water level measurements showed that the harbour’s Helmholtz pumping mode drives a 1-h period oscillation, which can influence flushing of the shallow embayments. This process likely persists year-round and would lead to flushing time-scales of between 1–11 days for these shallow embayments. If this ubiquitous pumping is combined with solar heat fluxes, it partially explains the persistent temperature gradients amongst the shallow embayments. In the larger and deeper (∼10 m) Inner Harbour, the prevailing westerly winds drive most of the mean circulation, with a current entering through the Western Gap and leaving through the Eastern Gap. This wind driven circulation leads to a residence time of water in the Inner Harbour between 7–14 days. In addition, periodic strong and sustained westerly winds can induce frequent upwelling events in Lake Ontario (between 4 to 10 times during the stratified season) that mildly increase the exchange flow and help maintain good water quality by exchange nearshore waters with cleaner hypolimentic waters. The intrusion of cold water into the harbour can also lead to highly variable temperature regimes with sudden drops in temperature that could have negative effects on aquatic organisms.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.997

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)0.0040.005

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 head0.257
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; both teacher heads agree on what is shown here.

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

Citations20
Published2018
Admission routes3
Has abstractyes

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