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Record W2146063109 · doi:10.18433/j3k89d

Hyaluronic Acid and Wound Healing

2015· review· en· W2146063109 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2015
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHyaluronic acidWound healingFibroblastMedicineRegeneration (biology)Tissue repairPharmacologyIn vitroSurgeryChemistryBiomedical engineeringBiochemistryBiologyCell biologyAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: We developed an experimental model of ethanol-induced dermatotoxicity and hepatocytoxicity using normal human keratinocytes and normal human hepatocytes that preserve inducible cytochrome p450 activities. The original work was described in several articles. The objective of this study was to determine whether hyaluronic acid attenuates skin necrosis, and to further clarify its uses in wound repair in humans, animal models and in vitro studies. METHODS: We performed a systematic review of the literature using the terms "hyaluronic acid" and "wound healing". PubMed was searched for studies published during the period 2010-2014. RESULTS: Hyaluronic acid is used in tissue regeneration alone or in combination with herbal or Western medicine. Scaffolds made up of hyaluronic acid were used to embed basic fibroblast growth factor. CONCLUSION: Hyaluronic acid extracts are safe and efficacious products to be used in skin repair.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.340
GPT teacher head0.549
Teacher spread0.210 · 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