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Record W3186940545 · doi:10.1177/12034754211032542

Soft Tissue Filler Therapy and Informed Consent: A Canadian Review

2021· review· en· W3186940545 on OpenAlexaffabout
John P. Arlette, Andrea L. Froese, Jaspreet Singh

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineInformed consentDocumentationFiller (materials)Medical recordFamily medicineAlternative medicineSurgery

Abstract

fetched live from OpenAlex

Soft Tissue Filler (STF) Therapy for cosmetic facial rejuvenation is associated with known complications. The manifestation of these known complications can lead to patients commencing civil litigation actions or making complaints to provincial regulatory authorities and alleging that the practitioner failed to obtain the patient's informed consent to the therapy. Data provided by the Canadian Medical Protective Association (CMPA) on medical-legal cases arising from the provision of STF therapy between 2005 and 2019 are presented. Select reported case law decisions from Canadian courts and regulatory bodies addressing the concept of informed consent are reviewed. Insights about the risk factors pertaining to the process of obtaining informed consent for STF therapy are presented to increase an understanding of the elements of communication and documentation needed to ensure patients are aware of the consequences of this treatment.

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)0.011
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.812
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.014
Science and technology studies0.0020.005
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.119
GPT teacher head0.384
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicFacial Rejuvenation and Surgery TechniquesFrench-language works237,207