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Record W2546746572 · doi:10.4047/jap.2016.8.5.345

Esthetic outcome for maxillary anterior single implants assessed by different dental specialists

2016· article· en· W2546746572 on OpenAlexaff
Abdullah Nasser Aldosari, Raed AlRowis, Feras Moslem, Fahad Ali Alshehri, Ahmed Ballo

Bibliographic record

VenueThe Journal of Advanced Prosthodontics · 2016
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProsthodontistPeriodontistMedicineDentistryVisual analogue scalePatient satisfactionOrthodonticsProsthodonticsPhysical therapySurgery

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to assess the esthetic outcome of maxillary anterior single implants by comparing the esthetic perception of dental professionals and patients. MATERIALS AND METHODS: Twenty-three patients with single implants in the esthetic zone were enrolled in this study. Dentists of four different dental specialties (Three orthodontists, three oral surgeons, three prosthodontists, and three periodontists) evaluated the pink esthetic score (PES)/white esthetic score (WES) for 23 implant-supported single restorations. The satisfactions of the patients on the esthetic outcome of the treatment have been evaluated according to the visual analog scale (VAS). RESULTS: <.01). Prosthodontists were found to have assigned poorer ratings among the other specialties, while oral surgeons gave the higher ratings than periodontists, orthodontists, and prosthodontists. CONCLUSION: Prosthodontists seemed to be stricter when assessing aesthetic outcome among other specialties. Moreover, a clear correlation existed between dentists' and patients' esthetic perception, thereby providing rationales for involving patients in the treatment plan to achieve higher levels of patient satisfaction.

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)0.001
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 score0.059
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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 designBench or experimental
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

Citations25
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Advanced ProsthodonticsSame topicDental Implant Techniques and OutcomesFrench-language works237,207