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Record W3132756805 · doi:10.1080/1040841x.2021.1884641

<i>Candida albicans</i>targets that potentially synergize with fluconazole

2021· review· en· W3132756805 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Reviews in Microbiology · 2021
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsConcordia University
FundersScience and Technology Commission of Shanghai Municipality
KeywordsFluconazoleCandida albicansCorpus albicansAntifungalMicrobiologyBiologyDrugPharmacology

Abstract

fetched live from OpenAlex

Fluconazole has characteristics that make it widely used in the clinical treatment of C. albicans infections. However, fluconazole has only a fungistatic activity in C. albicans, therefore, in the long-term treatment of C. albicans infection with fluconazole, C. albicans has the potential to acquire fluconazole resistance. A promising approach to increase fluconazole’s efficacy is identifying potential targets of drugs that can enhance the antifungal effect of fluconazole, or even make the drug fungicidal. In this review, we systematically provide a global overview of potential targets of drugs synergistic with fluconazole in C. albicans, identify new avenues for research on fluconazole potentiation, and highlight the promise of combinatorial strategies with fluconazole in combatting C. albicans infections.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.054
GPT teacher head0.373
Teacher spread0.318 · 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