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Record W2620645352 · doi:10.1097/psn.0000000000000182

Advances in Aesthetic Therapies: Plasma-Rich Protein Procedure for the Treatment of Alopecia

2017· article· en· W2620645352 on OpenAlex
Jeanine Harrison

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePlastic Surgical Nursing · 2017
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsNutrition InternationalThornhill Medical (Canada)
Fundersnot available
KeywordsHair lossPlatelet-rich plasmaIntensive care medicineMedicineHair growthHair removalDermatologyInternal medicinePhysiologyPlatelet

Abstract

fetched live from OpenAlex

Predominance of aesthetic options is growing and evolving to include procedures that have traditionally been much more invasive and fiscally challenging for the average patient. It is not uncommon now for the Canadian consumers to begin to look for lesser invasive options that show results significant enough to improve their appearance but that may not fall under the traditional health care coverage. One area that is evolving quickly is the nonsurgical treatment of hair loss. This is not a new condition, but generally the methods of treatment are not under the current health coverage; therefore, consumers are paying out of pocket to reduce or replace their hair loss. Recently, more options have evolved, and utilizing platelet-rich plasma has become more prevalent as a method to support hair growth and prevent hair loss.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.312

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 head0.019
GPT teacher head0.312
Teacher spread0.293 · 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