Three orthopaedic operations, over 1,000 randomized controlled trials, in over 100,000 patients
Bibliographic record
Abstract
In orthopaedic surgery, the three most commonly performed operations are total knee arthroplasty (TKA), total hip arthroplasty (THA), and anterior cruciate ligament reconstruction (ACLR). The demand for TKA is ever-increasing, with an estimated 700,000 TKAs performed each year in the USA alone, and a projected increase in demand to over 3.48 million procedures by 2030.1,2 Similarly, THA is one of the most successful and cost-effective interventions in orthopaedic surgery, considered by many as the operation of the century.3 The demand for THA is also rising worldwide.4-6 The anterior cruciate ligament (ACL) is the most commonly injured ligament in the knee with an estimated 400,000 ACLRs performed each year worldwide.7-9 Despite the success of and high demand for these procedures, debate continues on many surgical and technical aspects of these operations.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".