Bibliographic record
Abstract
The stratum corneum (SC) provides a vital barrier membrane between the external environment and the vulnerable internal tissues of the skin. It impedes the flow of water, the penetration of xenobiotics, and invasion of pathogenic micro-organisms. It also has protective capacity against ultraviolet radiation and thermal injury. As routine histopathology provides a misleading picture of a disorganized and shadowy SC, we would recommend the skin surface biopsy technique. This painless technique is easy and reliable in obtaining information from the SC. It demonstrates the geometric patterns of the surface, the openings of the eccrine ducts and hair follicles. The skin surface biopsy technique is also ideal for the investigation of the in situ microbiology of skin. Staining with periodic acid Schiff reagent makes it possible to see ringworm fungi, pityriasis versicolor, candida species, or erythrasma micro-organisms. Scanning electron microscopy can be employed when the higher magnification is needed. Histochemical applications include silver staining for melanin particle, potassium ferricyanide staining for blood pigments and lipid staining with Sudan red, for sebum. The rate of movement of topically applied drugs into the skin can be measured using the skin surface biopsy technique. The concentration of radiolabelled drugs can be counted and compared. Comedogenicity and DNA analysis are other applications of this non-invasive technique.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".