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Record W3135919426 · doi:10.25270/con.2021.01.00010

An Atlas of Lumps and Bumps, Part 1

2021· article· en· W3135919426 on OpenAlexaff
Benjamin Barankin, Alexander K. C. Leung, Joseph M. Lam, Kin Fon Leong

Bibliographic record

VenueConsultant · 2021
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryAlberta Children's Hospital
Fundersnot available
KeywordsPlantar wartsMedicineDermatologyHuman papillomavirusGenital wartsBarefootFoot (prosody)Human immunodeficiency virus (HIV)VirologyInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Plantar Warts P lantar warts (verrucae plantaris) are common cutaneous lesions on the plantar aspect of the foot that are caused by infection of keratinocytes by the human papillomavirus (HPV) types that are trophic to human skin.HPV types 1, 2, 4, 27, 57, 60, and 65 are the most common causes of plantar warts. [1]2][3] The annual incidence rate of plantar warts is estimated to be 14%. 4,5 The condition occurs most commonly in children and adolescents. 5 Females are affected more often than males. 2 Plantar warts shed HPV which can spread to other body sites (autoinoculation) or other people by close physical contact. 5 Plantar warts can also be acquired by walking barefoot on contaminated surfaces such as public shower floors, swimming pools, gym mats and locker rooms. 3 Moist environments and disruption of the epidermal barrier (eg, dry cracked heels) increase the chance of infection.Children with a family member or many classmates with warts have a higher risk of developing plantar warts themselves.The virus, however, does not spread to histologically dissimilar sites, such as the oral cavity and genitalia.Although the condition is seen primarily in healthy individuals, those with immunodeficiency are at increased risk for acquiring plantar warts and find it harder to clear their warts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.346
Teacher spread0.315 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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