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Record W2761467795 · doi:10.15171/joddd.2017.035

Preliminary study of a novel dental hand instrument for restorative procedures

2017· article· en· W2761467795 on OpenAlexaff
Les Kalman, Allen Xian

Bibliographic record

VenueJournal of Dental Research Dental Clinics Dental Prospects · 2017
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsWestern University
Fundersnot available
KeywordsInstrumentation (computer programming)Amalgam (chemistry)Task (project management)CarvingDentistryRestorative dentistryComputer scienceMedicineMedical physicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Background. There is no clear consensus on operative hand instrumentation. In general, there is one hand instrument that completes one task. Consequently, numerous instruments are required for the placement, shaping and carving of a restoration. This reduces clinical efficiency, increases cost and may generate frustration. Methods. A novel dental hand instrument has been developed. The instrument (GTI) can complete several tasks. The instrument was assessed in a laboratory setting with amalgam, composite and glass-ionomer restorations on dentoform teeth. Results. Results indicated that class II amalgam and composite restorations were significantly faster than conventional instrumentation (P<0.05). Differences in restoration quality were not statistically significant. Cost was significantly reduced as the GTI could perform the task of 9 conventional instruments. Conclusion. The GTI is an industry-translated, novel medical device that offers the clinician an alternative to standard instrumentation. Further investigations are required with increased samples sizes, clinical assessment and expanded utility.

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 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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0040.003
Research integrity0.0000.002
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 head0.186
GPT teacher head0.496
Teacher spread0.310 · 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 teacher head, not a consensus.

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

Citations2
Published2017
Admission routes1
Has abstractyes

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