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Record W2893048528 · doi:10.1136/jclinpath-2018-205388

Apoptotic colopathy: a pragmatic approach to diagnosis

2018· review· en· W2893048528 on OpenAlexaff
Dipti M. Karamchandani, Runjan Chetty

Bibliographic record

VenueJournal of Clinical Pathology · 2018
Typereview
Languageen
FieldMedicine
TopicMicroscopic Colitis
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineApoptosisBioinformaticsPathologyComputational biologyBiologyGenetics

Abstract

fetched live from OpenAlex

'Apoptotic colopathy' is an umbrella term signifying a pattern of injury where the gastrointestinal biopsy shows a colitic picture with apoptosis as the predominant histological feature. Although the entities within apoptotic colopathy share a common histological feature- 'apoptosis', there is a list of varied clinical differential diagnoses that produce this similar histological pattern of injury. These include graft-versus-host disease, drug-induced injury due to multiple drugs (in particular, mycophenolate mofetil, check point inhibitor therapy and some others), infections (particularly cytomegalovirus, adenovirus and some others), immune disorders and other miscellaneous causes. However, the management of these varied differentials is strikingly different, thus necessitating an algorithmic approach for accurate diagnosis and optimal patient management. A definitive diagnosis requires interpretation of varied histological findings in the appropriate clinical context including clinical history, drug history and laboratory findings. This review will focus on the histopathological findings of varied entities that can manifest as 'apoptotic colopathy' on assessment of colonic biopsies.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.002

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 head0.194
GPT teacher head0.513
Teacher spread0.319 · 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

Citations35
Published2018
Admission routes1
Has abstractyes

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