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Record W4309791390 · doi:10.1002/lno.12265

The dissolved oxygen budget of a small Canadian Shield lake during winter

2022· article· en· W4309791390 on OpenAlexaffabout
Alireza Ghane, Leon Boegman

Bibliographic record

VenueLimnology and Oceanography · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsQueen's University
Fundersnot available
KeywordsHypolimnionStratification (seeds)Environmental scienceEpilimnionTemperate climateConvective mixingHypoxia (environmental)Sink (geography)Atmospheric sciencesOxygenOceanographyConvectionNutrientGeologyEcologyChemistryBiologyMeteorologyEutrophication

Abstract

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Abstract Deep‐water hypoxia is an environmental concern in temperate lakes. Seasonal turnover events provide a mechanism for deep‐water oxygenation; however, the lake oxygen budget and mixing dynamics during turnovers are poorly understood. In the present study, the oxygen cycle in a small dimictic lake was investigated from long‐term field measurements supplemented with output from a three‐dimensional numerical model. Photosynthetic production and atmospheric exchange were modeled to predominate during spring and fall turnovers, respectively, contributing 92% (surprisingly) and 8% of the net dissolved oxygen (DO) input to the lake. Of the DO production, 41% occurred under‐ice, with a potential to supply 17% ± 11% of the hypolimnetic DO saturation deficit at spring turnover. The corresponding DO sinks were sediment oxygen demand (− 54%), mineralization (− 33%), and nitrification (− 13%). The watercolumn circulation and stratification during pre‐winter and spring turnover controlled the inter‐annual variability in hypoxia during the following summer. Warm winters (~ 4°C watercolumn leading to rapid summer stratification) and severely cold winters (strong winter stratification with shallow convective mixing in spring) were followed by incomplete spring turnover, whereas, following cold winters (moderate winter stratification and extended convection) turnover was complete. This underscores the connection between winter hydrodynamics and summer water quality in dimictic lakes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.162
Teacher spread0.156 · 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

Citations18
Published2022
Admission routes2
Has abstractyes

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