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Are Peripapillary Intrascleral Hemorrhages Pathognomonic for Abusive Head Trauma?*

2012· article· en· W1749315912 on OpenAlexaff
Candace H. Schoppe, Patrick E. Lantz

Bibliographic record

VenueJournal of Forensic Sciences · 2012
Typearticle
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsKronos (Canada)
Fundersnot available
KeywordsPathognomonicMedicineHead traumaSurgeryAccidentalChild abuseBlunt traumaPoison controlBluntInjury preventionEmergency medicineDiseasePathology

Abstract

fetched live from OpenAlex

The American Academy of Pediatrics' Committee on Child Abuse and Neglect, Section on Ophthalmology, acknowledges that searching for retinal hemorrhages (RHs) in infants only in cases of suspected of abuse creates selection bias. However, they also recommend that postmortem eye removal might not be indicated "in children who have clearly died from witnessed severe accidental head trauma or otherwise readily diagnosed systemic medical conditions." Although infrequently described in the child abuse literature, peripapillary intrascleral hemorrhages (bleeding in the sclera at the optic nerve insertion)--putatively from severe repetitive acceleration/deceleration forces with or without blunt head trauma--have been considered essentially pathognomonic for abusive head trauma (shaken baby syndrome). We present two neonates who sustained accidental, severe in utero head injuries and had associated extensive RHs and optic nerve sheath hemorrhages with peripapillary intrascleral hemorrhages detected at autopsy. Neither neonate had a documented clinical fundal examination in the intensive care unit.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.323
Teacher spread0.273 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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