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Record W2148544263 · doi:10.1136/bjo.2006.113878

The Halifax disaster (1917): eye injuries and their care

2007· article· en· W2148544263 on OpenAlexaffabout
Chryssa McAlister, T. J. Murray, H. Lakosha, Charles Maxner

Bibliographic record

VenueBritish Journal of Ophthalmology · 2007
Typearticle
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicineEnucleationAccidentalEye injuriesNova scotiaOptometryMedical emergencyPoison controlInjury preventionSurgeryHistory

Abstract

fetched live from OpenAlex

Explosions, man-made and accidental, continue to require improved emergency medical responses. In the 1917 Halifax Explosion, an inordinate number of penetrating eye injuries occurred. A review of their treatment provides insight into a traumatic event with unique ophthalmological importance. Archived personal and government documents relating to the Halifax Explosion were reviewed at the Public Archives of Nova Scotia, Canada, along with a review of current literature. Twelve ophthalmologists treated 592 people with eye injuries and performed 249 enucleations. Sixteen people had both eyes enucleated. Most of the eye injuries were caused by shards of shattered glass. A Blind Relief Fund was established to help treat and rehabilitate the visually impaired. The injured were given pensions through the Canadian National Institute for the Blind, Toronto, Ontario, Canada, which continue to this day. Sympathetic ophthalmia was the feared complication for penetrating eye injuries and a common indication for enucleation in 1917. Even so, the severity and the overwhelming number of eye injuries sustained during the Halifax Explosion made it impossible for lengthy eye-saving procedures to be performed. Enucleation was often the only option.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.012
GPT teacher head0.288
Teacher spread0.276 · 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

Citations12
Published2007
Admission routes2
Has abstractyes

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