Reproducibility of the Implant Crown Aesthetic Index – Rating Aesthetics of Single‐Implant Crowns and Adjacent Soft Tissues with Regard to Observer Dental Specialization
Bibliographic record
Abstract
AIM: The Implant Crown Aesthetic (ICA) Index evaluates the aesthetic outcome of implant-supported single crowns in the anterior zone by awarding nine points for the shape, color, and surface characteristics of the crowns and surrounding soft tissue. The aim of this study was to measure the reproducibility of the ICA Index and assess the influence exerted by the examiner's degree of dental specialization. MATERIALS AND METHODS: Ten examiners (two general dentists, two prosthodontists, two oral surgeons, two orthodontists, and two dental technicians) applied the ICA Index to 23 implant-supported single crowns twice at an interval of 4 weeks. The inter- and intra-examiner ratings were analyzed. Cohen's kappa (K) was used to measure the interexaminer reliability of estimations by two appraisers at a significance level of p < .05. RESULTS: Within the various parameters, the observer agreement ranged 53 to 81%. All the examiners achieved moderate agreement between the first and second ratings, whereby Cohen's kappa was 0.49 (p < .001). The most agreement was obtained by surgeons (K = 0.62, substantial) and the least by orthodontists (K = 0.24, sufficient). The lowest level of agreement with other occupational groups was manifested by the orthodontists (< or =44.3%). The ICA Index produced a moderate Cohen's kappa of 0.42 and agreement amounting to 67% between the two ratings within the occupational groups. There was minimum agreement among the occupational groups (Cohen's K = 0.11-0.37, observer agreement: 40.2-66.3%); again, the least agreement was between the orthodontists and others. CONCLUSIONS: The ICA Index resulted in poor to moderate intra- and interexaminer agreement. The validity and reproducibility of the ICA indexing as an objective tool in rating implant aesthetics is questionable.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".