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Performance of Dental Students Versus Prosthodontics Residents on a 3D Immersive Haptic Simulator

2014· article· en· W2305805912 on OpenAlex
Elizabeth J. Eve, Samuel Koo, Abdulmonem Alshihri, Jeremy Cormier, Maria Kozhenikov, R. Bruce Donoff, Nadeem Y. Karimbux

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

VenueJournal of Dental Education · 2014
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsInstitute of Infection and Immunity
FundersOffice of Naval Research
KeywordsProsthodonticsHaptic technologyDentistryFixed prosthodonticsVirtual realityCarious lesionContext (archaeology)Dental educationMedicineOrthodonticsSimulationPsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This study evaluated the performance of dental students versus prosthodontics residents on a simulated caries removal exercise using a newly designed, 3D immersive haptic simulator. The intent of this study was to provide an initial assessment of the simulator's construct validity, which in the context of this experiment was defined as its ability to detect a statistically significant performance difference between novice dental students (n=12) and experienced prosthodontics residents (n=14). Both groups received equivalent calibration training on the simulator and repeated the same caries removal exercise three times. Novice and experienced subjects' average performance differed significantly on the caries removal exercise with respect to the percentage of carious lesion removed and volume of surrounding sound tooth structure removed (p<0.05). Experienced subjects removed a greater portion of the carious lesion, but also a greater volume of the surrounding tooth structure. Efficiency, defined as percentage of carious lesion removed over drilling time, improved significantly over the course of the experiment for both novice and experienced subjects (p<0.001). Within the limitations of this study, experienced subjects removed a greater portion of carious lesion on a 3D immersive haptic simulator. These results are a first step in establishing the validity of this device.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.386
Teacher spread0.360 · 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