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Record W2086720844 · doi:10.1177/0272989x0102100301

Risk-Adjusted Monitoring of Binary Surgical Outcomes

2001· article· en· W2086720844 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

VenueMedical Decision Making · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicAdvanced Statistical Process Monitoring
Canadian institutionsActuaUniversity of Waterloo
Fundersnot available
KeywordsChartSurgical proceduresMedicineCUSUMControl chartComputer scienceCumulative riskStatisticsSurgeryMathematicsInternal medicine

Abstract

fetched live from OpenAlex

A graphical procedure suitable for prospectively monitoring surgical performance is proposed. The approach is based on accumulating evidence from the outcomes of all previous surgical patients in a series using a new type of cumulative sum chart. Cumulative sum procedures are designed to "signal" if sufficient evidence has accumulated that the surgical failure rate has changed substantially. In this way, the chart rapidly detects deterioration (or improvement) in surgical performance while not overreacting to the expected fluctuations due to chance. Through the use of a likelihood-based scoring method, the cumulative sum procedure is adapted so that it adjusts for the surgical risk of each patient estimated preoperatively. The procedure is therefore applicable in situations where it is desirable to adjust for a mix of patients. Signals of the chart lead to investigations of the cause and to the timely introduction of remedial measures designed to avoid unnecessary future failures.

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)0.005
metaresearch head score (Gemma)0.089
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.089
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.473
Teacher spread0.347 · 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