MétaCan
Menu
Back to cohort
Record W2809177716 · doi:10.5864/d2018-011

Profiling chlorine residuals using DPD and amperometric field test kits in a chlorinated small drinking water system with ammonia present in source water

2018· article· en· W2809177716 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEnvironmental Health Review · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsInuit Tapiriit KanatamiAlberta Health Services
Fundersnot available
KeywordsChlorineAmmoniaEnvironmental scienceChemistryWater treatmentRaw waterEnvironmental chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Effective chlorine residual monitoring of water treatment systems that have ammonia in the raw source water is crucial to ensure adequate disinfection. Understanding the limitations related to monitoring chlorine in these systems is important to help reduce risk from microbiological hazards. The presence of ammonia and the resulting chlorine demand can be very challenging to address in drinking water treatment, especially for small water systems. This study profiles a number of situations where erratic chlorine dosing, operational, and testing conditions create a false-positive free available chlorine result. This study identified that the field test kit using amperometric testing methodology is superior to the traditional DPD (N,N-diethyl-p-phenylene-diamine) tests in a water system that has the presence of ammonia with erratic chlorine dosage.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.240
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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