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Record W2792975772 · doi:10.21037/jlpm.2018.02.05

Laboratory diagnosis of Clostridium difficile infection

2018· article· en· W2792975772 on OpenAlexfundno aff
Katherine Kendrick

Bibliographic record

VenueJournal of Laboratory and Precision Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
FundersConsortium canadien en neurodégénérescence associée au vieillissementAmerican College of Gastroenterology
KeywordsClostridium difficilePseudomembranous colitisMicrobiologyMedicineAntibiotic-associated diarrheaDiarrheaAsymptomatic carrierAntibioticsToxic megacolonOutbreakAnaerobic bacteriaClostridium difficile toxin AClostridiumVirologyDiseaseInternal medicineBiologyBacteria

Abstract

fetched live from OpenAlex

Clostridium difficile infection (CDI) is a serious and sometimes life-threatening illness caused by toxin release from Clostridium difficile (CD), a gram-positive anaerobic bacterium. Infection with CD can cause clinical manifestations in a spectrum from asymptomatic carrier states to pseudomembranous colitis and toxic megacolon. Accurate diagnosis of CDI depends on early recognition of clinical symptoms of diarrhea, fever, and cramps especially after antibiotic use. Bacterial culture can be performed for epidemiological and antibiogram purposes during outbreaks of CDI. Culture, enzyme immunoassays (EIA), and molecular assays are useful for diagnosis of CDI. Toxigenic culture is useful to determine the cytopathic effect of the bacteria. Current Infectious Disease Society of America (IDSA) and American College of Gastroenterology (ACG) guidelines recommend using nucleic acid amplification tests or glutamate dehydrogenase (GDH) antigen followed by EIA testing for CD toxin A and B. Future studies for CDI diagnosis are looking toward toxin identification and the use of metabolomic analysis.

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)0.005
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: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.025
GPT teacher head0.330
Teacher spread0.304 · 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
GenreMethods

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

Citations3
Published2018
Admission routes1
Has abstractyes

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