Bibliographic record
Abstract
Commonly lost among personal preferences and scattered clinical results, ceramic implants have been commonly regarded as a therapeutic solution “of last recourse”, “holistic only” or “if the patient is allergic” procedures. While the clinical possibility of mechanical breakdown and the phantom of breakage and catastrophic failure has always been present, the aesthetic qualities of ceramic have been widely lauded. With alumina and other materials were randomly failing in clinical trials, the use of titanium reached new heights during the 90´s and early 2000´s. The 1981 Toronto conference set the tone for the development of new titanium surfaces, connections, and microgeometries, transforming dental practice and clinical protocols. In a quest to dominate the titanium dental implant market, it was an era of ambitious organizations such as NobelBioCare ™, Straumann ®, Astratech ®, Dentsply Sirona, Biomet 3i ® among others. Survival curves shot up to 98% and osseointegration time was cut in half (88/89 % for the machined Branemark implant). The “Titanium train” had left the station, more of a TGV than a steam locomotive with brand and market share (and demand from clinics) ruling out any possibility of the use of an alternative biomaterial.
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 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 | 0.071 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.022 | 0.012 |
| Insufficient payload (model declined to judge) | 0.035 | 0.013 |
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".