Cementless Total Knee Arthroplasty
Bibliographic record
Abstract
Update This article was updated on August 23, 2024, because of a previous error. On page 1, the following footnote was omitted but has since been included: *Yasir AlShehri, MD, and Panayiotis D. Megaloikonomos, MD, contributed equally to this work as first authors. An erratum has been published: JBJS Rev. 2024;12(7):e24.00064ER. » The demographic profile of candidates for total knee arthroplasty (TKA) is shifting toward younger and more active individuals. » While cemented fixation remains the gold standard in TKA, the interest is growing in exploring cementless fixation as a potentially more durable alternative. » Advances in manufacturing technologies are enhancing the prospects for superior long-term biological fixation. » Current research indicates that intermediate to long-term outcomes of modern cementless TKA designs are comparable with traditional cemented designs. » The selection of appropriate patients is critical to the success of cementless fixation techniques in TKA. » There is a need for high-quality research to better understand the potential differences and relative benefits of cemented vs. cementless TKA systems.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".