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Record W4410307800 · doi:10.35192/jjoas-n.v19i1.2033

The role of antimetabolite medication compared with traditional technique (cryotherapy) for treatment of verrucae

2025· article· en· W4410307800 on OpenAlexaff

Bibliographic record

VenueJordan Journal of Applied Science - Natural Science Series · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPowdery Mildew Fungal Diseases
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsCryotherapyAntimetaboliteMedicineDermatologySurgeryChemotherapy

Abstract

fetched live from OpenAlex

Background: Human papillomavirus, or HPV, is the cause of warts, which are benign skin and mucosal proliferations that typically affect the hands and feet. Due to innate immunity, warts in immune-competent individuals are benign and typically go away on their own in a matter of months or years. Fluorouracil, also known as 5-fluorouracil or 5-FU, belongs to the class of chemotherapy drugs used to treat various neoplasms. In addition, topical fluorouracil (5%) is Food and Drug Administration -approved for managing dermatologic conditions such as multiple actinic or solar keratoses and superficial basal cell carcinomas in cases where alternative methods are not feasible. Aim of the work: Compare the effectiveness of intralesional injections of 5-fluorouracil (5-FU) and cryotherapy for the treatment of plantar warts. Patients and Methods: 60 patients with many plantar warts (more than three warts) were involved in this randomized clinical research. Patients from dermatological clinic were recruited. Results: When treating palmoplantar warts, intralesional injections of 5-fluorouracil were equally effective as cryotherapy. Conclusion: A 5-FU intralesional injection proved to be effective in treating palmoplantar warts. For palmoplantar warts, cryotherapy is also a successful treatment. Keywords: Wart; Cryotherapy; 5-fluorouracil.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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