MétaCan
Menu
Back to cohort
Record W2104722322 · doi:10.1080/10934520902958757

Use of an oxygen-releasing compound to aerate eutrophic reservoir water

2009· article· en· W2104722322 on OpenAlexaff
Lee Hynes, Rob Jamieson, Graham A. Gagnon, Marianne Su‐Ling Brooks

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAerationErlenmeyer flaskAnoxic watersEutrophicationLaboratory flaskWater qualityEnvironmental scienceSedimentSurface waterOxygenEnvironmental engineeringWater bodyEnvironmental chemistryChemistryWaste managementGeologyNutrientEngineeringChromatographyEcologyBiology

Abstract

fetched live from OpenAlex

This study examined the use of an Oxygen Release Compound (ORC) as a slow release chemical aeration agent within eutrophic surface water systems. Bench and pilot-scale experiments involving ORC treatment of eutrophic reservoir water were conducted to determine operational properties of ORC and examine its performance as an aeration agent within a surface water environment. The bench-scale study involved the application of 10, 25 and 50 g ORC doses to 1 L Erlenmeyer flasks containing various water and sediment samples. The pilot-scale study involved a scaled up simulation of full-scale reservoir systems using large fiberglass tanks, where water quality parameters in an ORC-treated tank were compared to an untreated tank over a 4 month period. The results of these experiments indicate that the application of ORC can result in substantial increases in dissolved oxygen and pH when applied to deoxygenated water systems. Within the pilot scale study, a 300 g/m2 dose of ORC at the sediment water interface prevented the onset of anoxic conditions over a 4 month growing season period, releasing approximately 20% of its mass as oxygen within this time frame.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.291
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; 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 designBench or experimental
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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Science and Health Part ASame topicAquatic Ecosystems and Phytoplankton DynamicsFrench-language works237,207