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Record W2806815894 · doi:10.1177/1925362118782061

Fatty Liver and the Forensic Pathologist

2018· review· en· W2806815894 on OpenAlexaff
Christopher M. Milroy

Bibliographic record

VenueAcademic Forensic Pathology · 2018
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsFatty liverMedicineForensic pathologyAutopsySteatosisDiseasePathologySudden deathCause of deathLiver diseaseNonalcoholic fatty liver diseaseInternal medicinePhysiologyGastroenterology

Abstract

fetched live from OpenAlex

Fatty liver is a common finding in clinical practice and at autopsy. It is most commonly seen associated with alcohol abuse and in non-alcoholic fatty liver disease (NAFLD). It may also be seen in many other conditions in both adults and children. It is now recognized that NAFLD, like alcoholic liver disease, may lead to end stage liver disease. Nonalcoholic fatty liver disease is associated with increased mortality from other disorders, particularly cardiovascular diseases. Fatty liver may be seen in many conditions that concern autopsy pathologists, including drug toxicity, anorexia, hepatic ischemia, and heatstroke. In infants, steatosis is common in sudden unexpected deaths. Fatty liver has been associated with sudden death and this review examines the pathology and role of fatty liver in sudden death. Acad Forensic Pathol. 2018 8(2): 296-310

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.005

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 head0.064
GPT teacher head0.345
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2018
Admission routes1
Has abstractyes

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