MétaCan
Menu
Back to cohort
Record W2136944324 · doi:10.1080/15428110208984686

Exposures and Their Determinants in Radiographic Film Processing

2002· article· en· W2136944324 on OpenAlexaffabout
Kay Teschke, Yat Chow, Michael Bräuer, Ed Chessor, Bob Hirtle, Susan Kennedy, Moira Chan Yeung, Helen Ward

Bibliographic record

VenueAIHA Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversity of British Columbia
FundersHealth and Safety Executive
KeywordsGlutaraldehydeSulfur dioxideAcetic acidChemistryToxicologyWaste managementEngineeringEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Radiographers process X-ray films using developer and fixer solutions that contain chemicals known to cause or exacerbate asthma. In a study in British Columbia, Canada, radiographers' personal exposures to glutaraldehyde (a constituent of the developer chemistry), acetic acid (a constituent of the fixer chemistry), and sulfur dioxide (a byproduct of sulfites, present in both developer and fixer solutions) were measured. Average full-shift exposures to glutaraldehyde, acetic acid, and sulfur dioxide were 0.0009 mg/m3, 0.09 mg/m3, and 0.08 mg/m3, respectively, all more than one order of magnitude lower than current occupational exposure limits. Local exhaust ventilation of the processing machines and use of silver recovery units lowered exposures, whereas the number of films processed per machine and the time spent near the machines increased exposures. Personnel in clinic facilities had higher exposures than those in hospitals. Private clinics were less likely to have local exhaust ventilation and silver recovery units. Their radiographers spent more time in the processor areas and processed more films per machine. Although exposures were low compared with exposure standards, there are good reasons to continue practices to minimize or eliminate exposures: glutaraldehyde and hydroquinone (present in the developer) are sensitizers; the levels at which health effects occur are not yet clearly established, but appear to be lower than current standards; and health effects resulting from the mixture of chemicals are not understood. Developments in digital imaging technology are making available options that do not involve wet-processing of photographic film and therefore could eliminate the use of developer and fixer chemicals altogether.

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)0.003
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 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

Citations24
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueAIHA JournalSame topicOccupational exposure and asthmaFrench-language works237,207