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Record W1987556487 · doi:10.1259/dmfr/29518441

Time and motion study: a comparison of two photostimulable phosphor imaging systems used in dentistry

2006· article· en· W1987556487 on OpenAlexaff
Rajesh Ramamurthy, CF Canning, James P. Scheetz, A G Farman

Bibliographic record

VenueDentomaxillofacial Radiology · 2006
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsDalhousie University
Fundersnot available
KeywordsStopwatchMathematicsNuclear medicineOrthodonticsDentistryComputer scienceBiomedical engineeringMedicineStatistics

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare two photostimulable phosphor (PSP) dental radiographic systems in terms of time efficiency in making full mouth intraoral X-ray surveys (FMS). METHODS: PSP systems compared were (1) DenOptix) (Kavo/Gendex, Des Plaines, IL) and (2) ScanX) (Air Techniques, Hicksville, NY). Twenty one FMS of a DXTRR) Manikin (Dentsply, Des Plaines, IL) were made with each of the systems. Time for each procedural step was determined using a stopwatch. Steps studied were: (1) plate erasure; (2) packaging; (3) positioning/exposure; (4) unpacking, loading processor, scanning; and (5) image transfer to virtual FMS mount. The first six test runs for each system were excluded to eliminate the learning curve period influencing results. An independent groups t-test was employed for statistical analysis. The a priori was set at P< or =0.05. RESULTS: The total time involved in producing a FMS was not proven to be statistically significant comparing DenOptix) and ScanX). The mean procedure time for DenOptix) was 31.2 min; for ScanX) it was 27.1 min. While the processing time with ScanX) (mean time: 3.9 min) was shorter than for DenOptix) (mean time =7.8 min), the opposite was true for the image transfer to FMS format with the time much shorter with DenOptix) using VixWin) software (mean time =2.0 min) compared with ScanX) using Vipersoft) (mean time =3.9 min). The differences between the systems for these two steps did prove to be statistically significant (P< or =0.05). CONCLUSIONS: Although the mean time to make a FMS was slightly shorter on average with ScanX) than DenOptix), this difference was not proven to be statistically significant (P>0.05) in terms of time efficiency in producing a FMS.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.301
Teacher spread0.287 · 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

Citations16
Published2006
Admission routes1
Has abstractyes

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