MétaCan
Menu
Back to cohort
Record W2205319649 · doi:10.1562/2005-06-10-rn-570

The lodide/lodate Actinometer in UV Disinfection: Determination of the Fluence Rate Distribution in UV Reactors

2005· article· en· W2205319649 on OpenAlexaff
Ronald O. Rahn, James R. Bolton, Mihaela I. Stefan

Bibliographic record

VenuePhotochemistry and Photobiology · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsTrojan Technologies (Canada)
Fundersnot available
KeywordsActinometerTransmittanceAbsorbanceSPHERESQuartzAnalytical Chemistry (journal)ChemistryRADIUSOpticsTriiodideWavelengthFluenceYield (engineering)Materials scienceChromatographyComposite materialPhysicsElectrolyteIon

Abstract

fetched live from OpenAlex

Thirty-seven Suprasil quartz spheres, each approximately 1 cm in diameter and containing an iodide-iodate actinometric solution, were attached to a metal rack and inserted into a bench-scale UV reactor filled with water. The spheres were located at various distances and heights around a 12.4 W low-pressure Hg lamp housed inside a 3.2 cm-radius quartz sleeve in the middle of an annular batch reactor. UV light exposure at 254 nm was performed with the percent transmittance of the water present in the reactor at either 73% or 100% defined over a 1 cm path length. The spheres were simultaneously exposed to the UV light for a given period of time, after which the solutions were removed from the spheres and the yield of triiodide determined from the increase in absorbance at 352 nm. The resulting fluence rate at each site was then calculated on basis of the yield of triiodide. These results were compared with the predictions of a mathematical model based on the multiple point source summation approximation, including reflection and refraction at the air-quartz-water interface. Initially, the agreement was not satisfactory, especially in regions at an oblique angle to the lamp. The model was modified from a multiple point source model to a multiple cylindrical segment model by incorporating a cosine factor. The agreement between the new model and the experimental data was excellent and these experiments provide a strong validation of the model, even under conditions in which the fluence rate varied by >1000-fold between extreme sites in the reactor.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.597

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)0.0000.000

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations88
Published2005
Admission routes1
Has abstractyes

Explore more

Same venuePhotochemistry and PhotobiologySame topicMarine and coastal ecosystemsFrench-language works237,207