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Evaluation and comparison of dimensional stability of four interocclusal recording materials commonly available in India-An In-Vitro Study

2018· article· en· W2888911069 on OpenAlexaff
Jayaprakash Mugur Basavanna, Gurpreet Kaur, Ravikanth Haridas Jujare, Rana K Varghese

Bibliographic record

VenueJournal of PEARLDENT · 2018
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsMathematicsBiomedical engineeringMedicine

Abstract

fetched live from OpenAlex

An interocclusal record is a precise recording of a maxillo-mandibular position. Interocclusal recording materials are used to record the patient's maxillomandibular relationship in correct position. The dimensional stability of interocclusal recording materials is of utmost importance. But several materials are available commercially. Various studies have shown controversy over interocclusal recording material of choice. The study was conducted to evaluate and compare the dimensional stability of four commonly used interocclusal recording materials after one hour. Poly vinyl siloxane, polyether, zinc oxide eugenol and eugenol free zinc oxide were poured on a steel die of internal diameter of 3cm and the dimensional stability was measured using travelling microscope after 1hour and the data obtained were statistically analyzed. Eugenol free zinc oxide proved to be dimensionally stable with mean values of 2.487 after 1hour of time interval which was followed by polyether, polyvinyl siloxane and zinc oxide eugenol. Eugenol-free zinc-oxide paste was the most dimensionally stable interocclusal recording material as compared to polyether, polyvinyl siloxane and zinc oxide eugenol exhibiting no statistically significant difference between die scribes and those of the samples.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.064
GPT teacher head0.360
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

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