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Record W2037807690 · doi:10.1097/prs.0b013e3181d0ae58

Quality-Adjusted Life-Year as a Surgical Outcome Measure: A Primer for Plastic Surgeons

2010· article· en· W2037807690 on OpenAlexaffabout
Achilleas Thoma, Leslie L. McKnight

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsSt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineBiostatisticsFamily medicinePlastic surgeryEpidemiologyGeneral surgerySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Hamilton, Ontario, Canada From the Department of Clinical Epidemiology and Biostatistics and the Surgical Outcomes Research Center, McMaster University, and the Department of Surgery, Division of Plastic and Reconstructive Surgery, St. Joseph's Healthcare. Received for publication July 23, 2009; accepted October 29, 2009. Disclosure: No funding was received for this study. The authors have no financial interest to declare. Achilleas Thoma, M.D., M.Sc., 101-206 James Street South, Hamilton, Ontario L8P 3A9, Canada, [email protected]

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)0.019
metaresearch head score (Gemma)0.030
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: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.459

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.013
Science and technology studies0.0020.006
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.292
GPT teacher head0.400
Teacher spread0.108 · 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
GenreMethods

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

Citations26
Published2010
Admission routes2
Has abstractyes

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