MétaCan
Menu
← Back to cohort
Record W2360151922

Application of Vancouver Scale in the Treatment of Keloids with ~(90)Sr Radiation

2015· article· en· W2360151922 on OpenAlexaboutno aff
PU Xiao-ji

Bibliographic record

VenueBiaoji mianyi fenxi yu linchuang · 2015
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKeloidVascularityCure rateAdverse effectRadiation therapyDermatologySurgeryNuclear medicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective To explore the clinical curative effects of the treatment of keloids with90 Sr radiation and to choose adaptive indications by Vancouver scale. Methods 105 patients with 131 keloids were involved in this study. These keloids scored by VSS in color and luster,thickness,vascularity,softness and were divided into two groups( Group A 0 ~ 8,Group B 9 ~ 15). The patients were followed up for 6 to 12 months after the treatment with90 Sr radiation for efficacy evaluation. Results The cure rate of 131 keloids was 48. 09%,and the improve rate was 51. 91%,and the total effective rate was 51. 91%. The radiation dose in Group A was 23. 5 ± 8. 2Gy,and the cure rate was 62. 69%,the adverse effect rate was 16. 42%. The radiation dose in Group B was 35. 1 ± 6. 2Gy,and the cure rate was 32. 81%,the adverse effect rate was 48. 48%. Conclusion Vancouver scale is a simple,effect and accurate method to select the appropriate keloid patients for90 Sr applicator therapy.

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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.030
GPT teacher head0.313
Teacher spread0.283 · 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 designNon-randomized trial
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueBiaoji mianyi fenxi yu linchuang→Same topicDermatologic Treatments and Research→French-language works237,207→