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Record W2186318439 · doi:10.19070/2332-2977-1400012

Skin Diseases Among Sub-Saharan African Prisoners: The Cameroonian Profile

2014· article· en· W2186318439 on OpenAlexaff
Kouotou EA, Isidore Sieleunou, D Defo, Nansseu NJR, Atenkeng Apasew H, Moyou Somo R, Zoung-Kanyi Bissek AC

Bibliographic record

VenueInternational Journal of Clinical Dermatology & Research · 2014
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPrisonCapital cityCapital (architecture)GeographySituatedPoliticsSocioeconomicsPolitical scienceDemographyEnvironmental healthSociologyMedicineArchaeologyLaw

Abstract

fetched live from OpenAlex

To the best of our knowledge, no previous study has been conducted in Cameroon dedicated at evaluating the magnitude of skin diseases among prisoners.We therefore undertook the present survey, the aim of which was to determine the profile of skin-related diseases and infecions among Cameroonian prison inmates. MethodsThis was a cross-sectional study held during three months, from Febuary to April 2014, at the Mfou Pricipal Prison (MPP), one of the 6 main prisons located in the Centre region of Cameroon.Mfou is the capital city of the Mefou and Afamba division, situated 17 km away from the political capital of Cameroon, Yaoundé.Its prison was constructed in 1976 with a capacity of 100 inmates, but there were 369 prisoners present at the MPP during our study

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.078
GPT teacher head0.472
Teacher spread0.395 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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