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Record W2182305066

Prioritization for elective dental treatment under general anesthesia.

2007· article· en· W2182305066 on OpenAlexaff
Michael J Casas, David J. Kenny, Edward J Barett, L J Brown

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsPrioritizationMedicineQuality assuranceInter-rater reliabilityRanking (information retrieval)Reliability (semiconductor)Medical emergencyOperations managementComputer scienceProcess managementBusinessPsychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the process and outcomes of an initiative to develop a system to prioritize operating room bookings for children who require elective dental treatment. This initiative had 3 objectives: to improve the timeliness of treatment in the operating room based on medical and dental need, to provide a means to identify and expedite the highest-priority cases when operating room time became available, and to document the prioritization of cases as a quality assurance measure. Each patient booked for treatment in the operating room was assigned a priority ranking based on a combination of their medical risk and dental status. Measures of interrater reliability between clinician raters were moderate to good. Use of the prioritization system demonstrated improved timeliness of treatment for urgent cases and the effects of additional measures taken to reduce the waiting list.

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)0.009
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2007
Admission routes1
Has abstractyes

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