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.
Bibliographic record
Abstract
BACKGROUND: Microneedling is a relatively novel therapeutic modality introduced in the 1990s where small, fine needles are used to create micro punctures in the skin. It is a minimally invasive procedure used for various dermatological conditions, including androgenetic alopecia (AGA). OBJECTIVE AND METHODS: We comprehensively summarize the literature regarding microneedling in dermatology. We performed linear multivariable regressions to synthesize evidence from the clinical trials that investigated the efficacy of microneedling for AGA. Studies eligible for quantitative analyses were assessed for evidence quality. RESULTS: The exact mechanism of microneedling action is yet to be determined, with theories that include the wound-healing cascade. Microneedling monotherapy significantly increased total hair count more than topical minoxidil 5% (β = 12.29; p < 0.001). The combination treatment of microneedling with topical 5% minoxidil increased total hair count significantly compared to monotherapy with microneedling (β = 7.63, p < 0.05). Increasing the overall treatment duration of microneedling and reducing the frequency of microneedling sessions may positively influence an increase in total hair count. CONCLUSION: There are limited studies that investigate microneedling as a monotherapy for hair loss since majority of the trials combine it with other therapies such as topical minoxidil or platelet-rich plasma. While preliminary results look promising, further investigation of microneedling as a monotherapy in larger, randomized controlled trials will help determine its safety and efficacy, and place in treating AGA.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it