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Record W2054213427 · doi:10.1089/ees.2010.0243

Errors in Ultraviolet Fluence Calculations Due to Particles in Wastewater Samples

2010· article· en· W2054213427 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Engineering Science · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsUniversity of Toronto
FundersCanadian Water Network
KeywordsAbsorbanceUltravioletPath lengthFluenceIntegrating sphereEffluentWastewaterChemistryUltraviolet lightAnalytical Chemistry (journal)Environmental scienceOpticsChromatographyEnvironmental engineeringPhysicsIonPhotochemistry

Abstract

fetched live from OpenAlex

Conventional spectrophotometers that do not include an integrating sphere assembly do not account for scattered ultraviolet (UV) light in a water sample containing particles and can therefore overpredict absorbance. Water samples from the secondary effluent of a municipal wastewater treatment plant were monitored over the course of 1 year to determine whether the error introduced in UV absorbance measurements when neglecting scatter was significant. The error was interpreted in terms of UV fluence that would be calculated for varying path lengths of solution. The error ranged from 10% to over 90% and increased independently with total suspended solids and path length. Combination of increasing path length and total suspended solids, together, amplified the error. This study demonstrates that, in some situations, integrating sphere absorbance measurements may be warranted to minimize significant errors in estimated UV fluences; however, in other situations (e.g., short path lengths), conventional spectrophotometers may be sufficient.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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