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Record W2920669532 · doi:10.1128/microbe.7.483.1

Reviews and Resources:Infectious Diseases of the Skin

2012· article· en· W2920669532 on OpenAlex
Christian T. K.‐H. Stadtländer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrobe Magazine · 2012
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsSaint Paul University
Fundersnot available
KeywordsVirologyInfectious disease (medical specialty)Computer scienceMedicinePathologyDisease

Abstract

fetched live from OpenAlex

The skin is the largest organ system of the human body and requires special attention. It separates the inside of our body from the outside world, and thus acts as an important barrier against various types of environmental damage, including mechanical, chemical, and microbial. Elston's book deals with the damage caused by infectious agents such as bacteria, fungi, viruses, and arthropods. He prepared a highly illustrated guide that can be used to identify the most common infectious diseases of the skin. Elston points out that the visual examination of the skin is the most important task for the accurate identification of dermatologic diseases and that many criteria are used to establish a diagnosis, including morphology, symptoms, exposure, and time course. He also mentioned that although laboratory tests are important for providing confirmation of the diagnosis, “therapy must usually be initiated based on the initial clinical assessment.”

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.221

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)0.0000.000

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 head0.250
Teacher spread0.240 · 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