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Record W4366086718 · doi:10.1080/20442041.2023.2203060

Temporarily summer-stratified lakes are common: profile data from 436 lakes in lowland Denmark

2023· article· en· W4366086718 on OpenAlexaff
Martin Søndergaard, Anders Nielsen, Liselotte Sander Johansson, Thomas A. Davidson

Bibliographic record

VenueInland Waters · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsCommunitech
FundersHorizon 2020 Framework Programme
KeywordsStratification (seeds)BiotaWater columnTemperate climateEnvironmental scienceHydrology (agriculture)Thermal stratificationRange (aeronautics)Atmospheric sciencesPhysical geographyEcologyOceanographyGeologyGeographyBiology

Abstract

fetched live from OpenAlex

Lakes that undergo temporary stratification in summer do not fit into the classic categorisation of polymictic or dimictic lakes, but how common are they and what are the effects of stratification on the development of anoxia? We used monthly and bimonthly (twice per month) temperature and oxygen profile data from 436 Danish lakes (area range 1–3954 ha, maximum depth range 1.3–45 m) and defined a stratification indicator based on the temperature difference between the upper and lower 2 m of the water column. The stratification indicator had values between −1.6 and 17.7 °C and was significantly and strongly related to lake maximum depth and significantly but less strongly related to lake area. The indicator was highly variable, especially in lakes with maximum depths between 4 and 10 m, where intermediate indicator values suggest one or several mixing events during summer. The dissolved oxygen concentration in summer at the bottom was often <1 mg/L, even when the difference between top and bottom temperature was as low as 0.5–1.0 °C. Temporarily stratifying lakes with frequent mixing events over the summer are probably common in temperate lowland areas but are easily overlooked in routine monitoring programs. Temporary stratification has pronounced implications for the oxygen concentrations and potentially also for the biota and interactions between sediment and water.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.042
GPT teacher head0.261
Teacher spread0.219 · 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.

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

Citations16
Published2023
Admission routes1
Has abstractyes

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