Time and motion study: a comparison of two photostimulable phosphor imaging systems used in dentistry
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".