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Record W2334156434 · doi:10.1097/prs.0b013e318221f2ec

Designing and Reporting Case Series in Plastic Surgery

2011· review· en· W2334156434 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.

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2011
Typereview
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSeries (stratigraphy)Randomized controlled trialHierarchyClinical study designResearch designAffect (linguistics)MedicineComputer scienceMedical physicsSurgeryPsychologyClinical trialMathematicsStatisticsPathology

Abstract

fetched live from OpenAlex

The case series is the most prevalent type of clinical research in the plastic surgery literature. However, this is a lower level study design in the hierarchy of evidence. The case series is nevertheless a useful hypothesis generator for future studies. These in turn can be tested with more robust study designs such as the randomized controlled trial. Because the case series remains the most common study design used to communicate our new innovations, there is a need to improve its reporting so that readers will know why the study was undertaken, what the results were, and how the results affect patient care. The authors provide a guide to help future investigators improve the conduct and the reporting of their case series.

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)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-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 score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.141
GPT teacher head0.332
Teacher spread0.191 · 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