MétaCan
Menu
Back to cohort

Factors influencing optical 3D scanning of vinyl polysiloxane impression materials

2001· article· en· W2128067760 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Prosthodontics · 2001
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial Research
KeywordsImpressionSurface roughnessMaterials scienceComputer graphics (images)Sample (material)SoftwareComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

PURPOSE: Future growth in dental practice lies in digital imaging enhancing many chairside procedures and functions. This revolution requires the fast, accurate, and 3D digitizing of clinical records. One such clinical record is the chairside impression. This study investigated how surface angle and surface roughness affect the digitizing of vinyl polysiloxane impression materials. MATERIALS AND METHODS: Seventeen vinyl polysiloxane impression materials were digitized with a white light optical digitizing system. Each sample was digitized at 3 different angles: 0 degrees, 22.5 degrees, and 45 degrees, and 2 digitizer camera f-stops. The digitized images were rendered on a computer monitor using custom software developed under NIH/NIDCR grant DE12225. All the 3D images were rotated to the 0 degrees position, cropped using Corel Photo-Paint 8 (Corel Corp, Ottawa, Ontario, Canada), then saved in the TIFF file format. The impression material area that was successfully digitized was calculated as a percentage of the total sample area, using Optimas 5.22 image processing software (Media Cybernetics, LP, Silver Spring, MD). The dependent variable was a Performance Value calculated for each material by averaging the percentage of area that digitized over the 3 angles. New samples with smooth and rough surfaces were made using the 7 impression materials with the largest Performance Values. These samples were tested as before, but with the additional angle of 60 degrees. Silky-Rock die stone (Whip Mix Corp, Louisville, KY) was used as a control. RESULTS: The Performance Values for the 17 impression materials ranged from 0% to 100%. The Performance Values for the 7 best materials were equivalent to the control at f/11 out to a surface angle of 45 degrees; however, only Examix impression material (GC America Inc, Alsip, IL) was equivalent to the control at f/11/\16. At the 60 degrees surface angle with f/11/\16, the Performance Values were 0% for all the impression materials, whereas that for the control was 90%. The difference in the Performance Values for the smooth and rough surface textures was 7%, which was not significant. CONCLUSIONS: The digitizing performance of vinyl polysiloxane impression materials is highly material and surface angle-dependent and is significantly lower than the die stone control when angles to 60 degrees are included. It is affected to a lesser extent by surface texture.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.040
GPT teacher head0.317
Teacher spread0.277 · 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