MétaCan
Menu
Back to cohort
Record W1799062390 · doi:10.1556/maseb.60.2007.2.1

A kóros hegek kezelésének és megelőzésének lehetőségei napjainkbanr

2007· review· hu· W1799062390 on OpenAlexaboutno aff
O Kelemen, Lajos Kollár

Bibliographic record

VenueMagyar Sebészet (Hungarian Journal of Surgery) · 2007
Typereview
Languagehu
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKeloidDermatologyCryosurgeryRandomized controlled trialScarsSurgeryHypertrophic scars

Abstract

fetched live from OpenAlex

The aetiology of pathologic scarring is unknown today regarding the keloids. The authors have analyzed the literature and own experience retrospectively according to the evidence based treatments and prevention of the hypertrophic and keloid scars. The corticosteroids have been used intralesionally since the beginning of the 1960-ies. It was followed by the pressure garment therapy in order to treat the widespread burns scars in the early 1970-ies. The silicone gel sheeting is being used since the 1980-ies. The basic treatment of keloids changed, radiotherapy was combined with the above mentioned methods because of its high recurrence rate. Newer methods, cryosurgery as well as lasers were used to treat keloids. The number of effective topical agents was increased. The researchers have been looking for other, intralesionally usable medicine and genetic causes for more than ten years. The clinicians have had the standard protocols of the adjunct and alternative methods too. After having the standard and internationally accepted scar assessment system (Vancouver-scar scale and score), the controlled, randomized trials were practicable. The prospective evaluation of the efficacy of different protocols with adequate follow-up became performable. The comparison of different methods is difficult because of the lack of its standard outcome.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.804
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0110.006
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0060.003

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 head0.240
GPT teacher head0.415
Teacher spread0.174 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueMagyar Sebészet (Hungarian Journal of Surgery)Same topicDermatologic Treatments and ResearchFrench-language works237,207