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Record W2345556806 · doi:10.1097/icb.0000000000000323

ACANTHAMOEBA ENDOPHTHALMITIS AFTER RECURRENT KERATITIS AND NODULAR SCLERITIS

2016· article· en· W2345556806 on OpenAlexafffund
Zaid Mammo, David R.P. Almeida, Matthew A. Cunningham, Eric K. Chin, Vinit B. Mahajan

Bibliographic record

VenueRetinal Cases & Brief Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaResearch to Prevent Blindness
KeywordsAcanthamoeba keratitisAcanthamoebaMedicineEndophthalmitisScleritisContact lensKeratitisEnucleationSurgeryDermatologyOphthalmologyMicrobiologyBiologyUveitis

Abstract

fetched live from OpenAlex

PURPOSE: To describe the clinical course of a patient with Acanthamoeba keratitis, who despite prompt treatment progressed to histopathology-confirmed Acanthamoeba retinitis and endophthalmitis. METHODS: Case report. RESULTS: A healthy 30-year-old male wearing soft contact lens was diagnosed with Acanthamoeba keratitis and treated medically and surgically over the course of 1 year with presumed resolution of the infection. Yet, his infection recurred with documented spread to sclerokeratitis, and overwhelming endophthalmitis. Concerns about extra-ocular spread prompted a therapeutic enucleation with histopathologic evidence of Acanthamoeba organisms throughout the globe. CONCLUSION: This is a case of a severe recurrent Acanthamoeba infection presenting initially as keratitis, followed by sclerokeratitis and histolopathology-confirmed endophthalmitis. This case demonstrates that despite persistent medical and surgical intervention, eradication of organisms may not be possible.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

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