Immediate/Early Loading of Dental Implants: a Report from the Sociedad Espanola de Implantes World Congress Consensus Meeting in Barcelona, Spain, 2002
Bibliographic record
Abstract
BACKGROUND: Immediate/early loading protocols are becoming frequently used in implant dentistry, but the prerequisites for achieving good results and the limitations of such protocols are not fully known. Moreover, the terminology used in immediate/early loading is still confusing. PURPOSE: The purpose of this article is to present the outcome of a consensus meeting on immediate/early loading. MATERIALS AND METHODS: A consensus meeting was organized during the Sociedad Española de Implantes World Congress in Barcelona on May 23, 2002, with the objective to present and discuss the experiences from immediate/early loading protocols in dental implant treatment. The purpose was also to discuss definitions of the terminology used in immediate/early loading. The consensus meeting agenda included presentations from invited experts, followed by a consensus discussion. RESULTS: A consensus statement was agreed on. CONCLUSIONS: Multiple independent investigators have demonstrated that immediate/early loading of implants is possible in many clinical situations; however, additional documentation is required.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".