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Record W1973935887 · doi:10.1016/j.ijid.2014.07.009

The chronic enteropathogenic disease schistosomiasis

2014· review· en· W1973935887 on OpenAlexfundno aff
David U. Olveda, Remigio M. Olveda, Donald P. McManus, Pengfei Cai, Thao N.P. Chau, Alfred K. Lam, Yuesheng Li, Donald A. Harn, Marilyn L. Vinluan, Allen G. Ross

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsnot available
FundersMedical Research CouncilNational Institutes of HealthNational Health and Medical Research CouncilInternational Development Research Centre
KeywordsSchistosomiasisSchistosoma haematobiumMedicineSchistosomaParasitic diseaseDiseaseImmunologyLiver biopsyChronic liver diseaseFibrosisPathologySchistosoma mansoniBiopsyGastroenterologyHelminths

Abstract

fetched live from OpenAlex

Schistosomiasis is a chronic enteropathogenic disease caused by blood flukes of the genus Schistosoma. The disease afflicts approximately 240 million individuals globally, causing approximately 70 million disability-adjusted life years lost. Chronic infections with morbidity and mortality occur as a result of granuloma formation in the intestine, liver, or in the case of Schistosoma haematobium, the bladder. Various methods are utilized to diagnose and evaluate liver fibrosis due to schistosomiasis. Liver biopsy is still considered the gold standard, but it is invasive. Diagnostic imaging has proven to be an invaluable method in assessing hepatic morbidity in the hospital setting, but has practical limitations in the field. The potential of non-invasive biological markers, serum antibodies, cytokines, and circulating host microRNAs to diagnose hepatic fibrosis is presently undergoing evaluation. This review provides an update on the recent advances made with respect to gastrointestinal disease associated with chronic schistosomiasis.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.012
GPT teacher head0.332
Teacher spread0.320 · 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

Citations101
Published2014
Admission routes1
Has abstractyes

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