Short-term efficacy of calcium fructoborate on subjects with knee discomfort: a comparative, double-blind, placebo-controlled clinical study
Bibliographic record
Abstract
Calcium fructoborate (CFB) at a dose of 110 mg twice per day was previously reported to improve knee discomfort during the first 14 days of treatment. In this study, 60 participants with self-reported knee discomfort were randomized into two groups receiving CFB or placebo. Initial levels of knee discomfort were evaluated by Western Ontario and McMaster Universities Arthritis Index (WOMAC) and McGill Pain Questionnaire (MPQ) scores at the beginning of the study and also at 7 and 14 days after treatment. Results showed that supplementation with CFB significantly improved knee discomfort in the study subjects; significant reductions of mean within-subject change in WOMAC and MPQ scores were observed for the CFB group compared to the placebo group at both 7 and 14 days after treatment. Estimated treatment differences for the MPQ score were -5.8 (P=0.0009) and -8.9 (P<0.0001) at Day 7 and 14, respectively. Estimated differences for the WOMAC score were -5.3 (P=0.06) and -13.73 (P<0.0001) at Day 7 and 14, respectively. Negative values indicate greater reductions in reported discomfort. On both Day 7 and Day 14, the trend was toward greater improvement in the CFB group. The placebo group did not exhibit any change in the WOMAC and MPQ scores. In conclusion, supplementation with 110 mg CFB twice per day was associated with improving knee discomfort during the 2 weeks of intake.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".