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Record W2102353840 · doi:10.18433/j3831v

Phyto-Extracts in Wound Healing

2013· review· en· W2102353840 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2013
Typereview
Languageen
FieldMedicine
TopicPapaya Research and Applications
Canadian institutionsnot available
FundersBiogen
KeywordsWound healingGranulation tissueAngiogenesisAntimicrobialChemistryInflammationScaffoldCell biologyTraditional medicineBiochemistryBiologyMedicineBiomedical engineeringSurgeryImmunologyCancer research

Abstract

fetched live from OpenAlex

Data generated through systematic investigation, carried out on the evaluation of phyto-extracts on wound healing research during the last 20 years have been compiled. About 450 plant species having wound healing properties have been identified. The present knowledge of the wound healing process comprise coagulation, inflammation, proliferation, formation and accumulation of fibrous tissues, collagen deposition, epithelialization, contraction of wound with formation of granulation tissues, remodeling and maturation. The constituents of the plant extracts modulate one or more of the above stages. It was the endeavor to identify the active constituents responsible for antimicrobial activity, free radical scavenging properties, stimulators of enhanced collagen production and/or angiogenesis promoters with identification of lead scaffold chemical structures. Multiple phytochemicals concentrated and blended in optimal concentrations, are expected to be available in future years to carry out multi-tasking efforts in wound healing as more knowledge about the properties of the key constituents are unveiled.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · 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
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.391
GPT teacher head0.583
Teacher spread0.192 · 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