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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 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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0830.038

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 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
GenreOther

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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