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Record W2091440989 · doi:10.1139/w05-148

Predisposing conditions for<i>Candida</i>spp. carriage in the oral cavity of denture wearers and individuals with natural teeth

2006· article· en· W2091440989 on OpenAlexvenueno aff
Juliana Pereira Lyon, Sérgio Carvalho da Costa, Valéria Maria Gomes Totti, Maira Forestti Vieira Munhoz, Maria Aparecida de Resende

Bibliographic record

VenueCanadian Journal of Microbiology · 2006
Typearticle
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCarriageOral cavityDentistryMicrobiologyMedicineBiologyPathology

Abstract

fetched live from OpenAlex

Candida species are a normal commensal present in a large percentage of healthy individuals. Denture wearers are predisposed to the development of candidosis and to the presence of Candida spp. The presence of the yeast, even in healthy subjects, should be considered more carefully. We investigated the prevalence of Candida spp. in 112 denture wearers and 103 individuals with natural teeth, patients from the clinic of total prosthesis of the Dental School of the Federal University of Minas Gerais, Brazil, and from the School of Pharmacy and Dentistry of Alfenas, Brazil. Factors like gender, age over 60 years, low education, and xerostomia were directly associated with the presence of Candida yeasts at a significance level of 5% (p > 0.05). However, the major predisposing factor for the carrier state was wearing dentures (p = 0.001). Candida isolates were identified using morphological and biochemical profiles. Seventy-one isolates were identified as C. albicans (65.1%), 15 as C. glabrata (13.7%), 8 as C. parapsilosis (7.3%), 3 as C. krusei (2.7%), and 12 as C. tropicalis (11.0%). Susceptibility testing to fluconazole and itraconazole was also performed with the strains obtained. Both drugs showed a strong inhibition against most oral isolates.

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: Observational · Consensus signal: Observational
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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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 designObservational
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

Citations63
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of MicrobiologySame topicDental Trauma and TreatmentsFrench-language works237,207