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Irrigation rates and handpieces used in prosthodontic and operative dentistry: Results of a survey of North American dental school teaching

2000· article· en· W2043108595 on OpenAlexaboutno aff
Sharon C. Siegel, J.A. von Fraunhofer

Bibliographic record

VenueJournal of Prosthodontics · 2000
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsFixed prosthodonticsDentistryMedicineProsthodonticsDental instrumentsOrthodontics

Abstract

fetched live from OpenAlex

PURPOSE: A data baseline on dental cutting methodologies was established by means of a survey of North American dental school teaching. MATERIALS AND METHODS: Sixty-four North American dental schools were surveyed regarding their recommendations on handpiece usage and coolant flow rates in fixed prosthodontics and operative dentistry. RESULTS: High-speed handpieces were the instruments of choice for tooth preparation in fixed prosthodontics. In operative procedures, recommendations for sole use of the high-speed, the low-speed, or both handpiece types were more uniform. CONCLUSIONS: North American dental schools advocate greater use of high-speed than low-speed handpieces. Although the use of high-speed handpieces predominate in schools in Canada and Puerto Rico, there is a proportionately higher use of low-speed handpieces than in US dental schools. Few (approximately 1 in 5) schools made recommendations on coolant flow rates during cutting procedures.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.381
Teacher spread0.330 · 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
Published2000
Admission routes1
Has abstractyes

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