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Record W3046320131 · doi:10.1177/2292550320936695

Dr Patricia Clugston—A Spirit of Determination

2020· article· en· W3046320131 on OpenAlexaffabout
Yaeesh Sardiwalla, Christina Weber, Steven F. Morris

Bibliographic record

VenuePlastic Surgery · 2020
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsDalhousie UniversityMcMaster University
Fundersnot available
KeywordsArtPsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

Dr Patricia Clugston was a British Columbia native who completed her plastic surgery residency training in Vancouver in 1993 before pursuing a fellowship in Nashville with Dr Patrick Maxwell in 1994. When Dr Clugston returned to Vancouver, she helped to establish a comprehensive and renowned breast reconstruction program. She spent her career advocating for and working towards better treatment options for women seeking breast reconstruction. As a determined surgeon and accomplished athlete, Dr Clugston was truly a tour de force in all aspects of her life. Patty, as she was affectionately known by her colleagues, loved her job. Dr Clugston was an avid advocate for medical education and an outstanding clinical researcher and speaker that established her as a shining star in Canadian plastic surgery. Patty had always lived life to the fullest and was determined that scleroderma would not change this. Her sharp wit, intellectual curiosity, and pragmatism masked an incredible courage as she fought bravely against a cruel disease. Dr Clugston died on March 1, 2005, at the age of 46 surrounded by the loving company of her husband, friends, and family at the Vancouver General Hospital. The Dr Patricia Clugston Chair in Breast Reconstruction was established in her name to honour her legacy and continue to improve the care of patients with breast cancer.

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)0.004
metaresearch head score (Gemma)0.026
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.006
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0030.015
Insufficient payload (model declined to judge)0.0130.005

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 head0.101
GPT teacher head0.396
Teacher spread0.295 · 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
GenreOther

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

Citations0
Published2020
Admission routes2
Has abstractyes

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