Biochemical analyses of human osteoarthritic and periprosthetic synovial fluid
Bibliographic record
Abstract
Biochemical analyses were performed on osteoarthritic and periprosthetic synovial fluid in order to propose changes to lubricant specifications currently outlined in orthopaedic wear testing standards. Osteoarthritic and periprosthetic synovial fluid samples were obtained from the hip and knee joints of 40 patients. The samples in each group were analysed and compared in order to identify differences between the protein concentration, constituent fractions, osmolality, thermal stability and the hyaluronic acid concentration and molecular weight distribution of osteoarthritic and periprosthetic synovial fluid. The average total protein concentration was approximately 30 g/L, which was much higher than the 20 g/L currently specified in the knee wear testing standard; however, the 30 g/L protein concentration matched the recently revised standard for hip simulator wear testing. No significant difference was found between the protein concentration, osmolality, thermal stability, and hyaluronic acid concentration of osteoarthritic and periprosthetic synovial fluid. The clinical data provided should be used to better define the composition of a more clinically relevant lubricant for orthopaedic wear testing.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".