Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: To assess the effect of botulinum toxin A (BTA) for treating neuropathic pain in patients with spinal cord injury (SCI). METHODS: A total of 44 patients with SCI with neuropathic pain were randomly divided into the intervention group and the placebo group, each group 21 patients. The subjects in the intervention group received BTA (200 U subcutaneous injection, once daily) at the painful area, whereas those in the placebo group were administered a saline placebo. This study was conducted from December 2014 to November 2016. The primary outcome was measured using the visual analog scale (VAS). The secondary outcomes were measured using the short-form McGill Pain Questionnaire (SF-MPQ), and World Health Organization quality of life (WHOQOL-BREF) questionnaire. All outcome measurements were performed before and after 4 and 8 weeks of intervention. RESULTS: Forty-one participants completed the study. The intervention with BTA showed greater efficacy than placebo in decreasing the VAS score after week 4 and week 8 of treatment. Significant differences in the SF-MPQ and WHOQOL-BREF were also found between the 2 groups. CONCLUSION: The results of this study demonstrated that BTA might decrease intractable neuropathic pain for patients with SCI.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.419 | 0.286 |
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".