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Feasibility of Bubble Plume Destratification of Central Lake Erie

2012· article· en· W2053771260 on OpenAlex
Leon Boegman, Sylvia Sleep

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Hydraulic Engineering · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of Toronto
FundersNational Oceanic and Atmospheric Administration
KeywordsStratification (seeds)PlumeEnvironmental scienceWater columnHydrology (agriculture)BubbleStructural basinMixing (physics)Hypoxia (environmental)OceanographyMeteorologyAtmospheric sciencesGeologyMechanicsOxygenGeotechnical engineeringGeomorphologyGeography

Abstract

fetched live from OpenAlex

The central basin of Lake Erie has chronic hypoxia that is exacerbated by strong seasonal temperature stratification near the lake bed. A computational study was conducted to determine the feasibility of mechanically mixing the water column by using a bubble plume system to reduce stratification, thus facilitating vertical transport of oxygen. The most efficient design delivered an air flow rate of 0.4–0.5 m3 s−1 through 40–50 non-interacting plumes, which only mix the watercolumn during the late summer hypoxic events. The optimal efficiency was computed using a new metric, which neglects changes in stratification resulting from meteorologically induced mixing, relative to those from artificial mixing.

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.

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 score0.126
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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