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Record W2086040840 · doi:10.5402/2012/351603

Common Dermatoses in Children Referred to a Specialized Pediatric Dermatology Service in Mexico: A Comparative Study between Two Decades

2012· article· en· W2086040840 on OpenAlexaff
Blanca R. Del Pozzo‐Magaña, Alejandro Lazo‐Langner, Pedro Gutiérrez‐Castrellón, Ramón Ruiz‐Maldonado

Bibliographic record

VenueISRN Dermatology · 2012
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsWestern UniversityChildren’s Health Research Institute
Fundersnot available
KeywordsDermatologyMedicineAtopic dermatitisAcneEpidemiologyDemographicsMelasmaPediatricsPathologyDemography

Abstract

fetched live from OpenAlex

Background. Skin diseases among pediatric patients differ from those in adults. Epidemiological studies are scarce, and those performed in Mexican population date back thirty years. It is likely that these diseases might have changed their frequency. Material and Methods. Retrospective study in first-time patients referred to a pediatric dermatology service between January 1994 and December 2003. Demographics and diagnosis were recorded and compared with the results of a previous study performed in the same institution. Results. We included 5250 patients (52.55% female, 47.47% male) with 6029 diagnoses. The most frequent dermatoses found were atopic dermatitis (14.59%), viral warts (6.62%), acne (5.53%), pityriasis alba (3.98%), melanocytic nevi (3.85%), xerosis (3.57%), keratosis pilaris (3.19%), seborrheic dermatitis (2.37%), hemangioma (2.26%), and papular urticaria (2.24%). Most dermatoses increased their frequency when compared to the previous study. Conclusion. The frequency of pediatric dermatoses in our institution has changed in the last two decades. Environmental and sociocultural factors and institutional policies might account for these results.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.049
GPT teacher head0.380
Teacher spread0.331 · 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

Citations46
Published2012
Admission routes1
Has abstractyes

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