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Record W4408997637 · doi:10.1093/rpd/ncaf025

A curious case: a criminal exposure to X-rays

2025· article· en· W4408997637 on OpenAlexaff
Jacques Blanchette, Farah Nasser, Yvan Dutil

Bibliographic record

VenueRadiation Protection Dosimetry · 2025
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalSanté MontérégieCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanMontreal Heart InstituteInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsCommitLaw enforcementEvent (particle physics)Government (linguistics)EnforcementIntervention (counseling)BusinessComputer securityCriminologyPsychologyLawPublic relationsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

In 1989, following a workplace conflict, a worker activated an industrial radiography generator exposing a colleague to a significant amount of ionizing radiation. To our knowledge, this is the only documented case where an X-ray machine was used to commit a criminal act. Since the incident, 35 years have passed. Using the scientific information gathered at the time, we have attempted to create the clearest possible picture of this event. Although scientific knowledge has advanced since then, the overall assessment remains unchanged. An important lesson to be drawn from this crime is the significance of taking early actions to identify the level of exposure and ensure timely intervention to minimize the consequences for the victim. Another takeaway from this event is the numerous challenges the worker faced in having his situation acknowledged by both law enforcement authorities and various government agencies, given the unique nature of the incident.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0120.004
Scholarly communication0.0030.002
Open science0.0020.004
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.298
Teacher spread0.285 · 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 designCase report
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

Citations0
Published2025
Admission routes1
Has abstractyes

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