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2000· article· en· W4232461650 on OpenAlexaboutno aff
Mary A. Parmelee

Bibliographic record

VenueAmerican Water Works Association · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceWastewaterWaste managementBioaugmentationPersonal protective equipmentEnvironmental engineeringProcess engineeringPulp and paper industryEngineeringContaminationCoronavirus disease 2019 (COVID-19)Ecology

Abstract

fetched live from OpenAlex

Topics covered in this column include: bioaugmentation, the addition of billions of microorganisms to wastewater to achieve a range of process objectives such as improved operational efficiency and reduced levels of ammonia, grease, sludge, and odors; a new water treatment facility in Lake Havasu City, Arizona, that will be the first in the US to use biological treatment to remove manganese; an innovative and economical sidestream ozone injection system designed to disinfect drinking water in high‐pressure applications for the Greater Vancouver Water District; and, a personal immersion system (PIS) that consists of two conventional personal computers and two standard projectors with a special projection screen and interaction equipment.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.261
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7390.742

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 head0.008
GPT teacher head0.223
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2000
Admission routes1
Has abstractyes

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