Knowledge and management of snake bite by general practitioners in rural Free State and Northern Cape
Bibliographic record
Abstract
Background: The aim of the study was to determine the knowledge of general practitioners in the rural areas of the Free State and Northern Cape regarding snake bites and their treatment. Methods: Telephonic interviews using structured questionnaires were conducted with a random sample of 50 general practitioners from rural areas in each region. Results: Doctors in each region indicated that they knew the snakes in their region (Free State 93.6% and Northern Cape 91.8%), but only 17% of the Free State and 53.1% of the Northern Cape doctors felt that they knew enough about the treatment of snake bites. More than three quarters of the Northern Cape doctors have polyvalent antiserum available and 49% have used it, compared to only 40.4% of Free State respondents who have polyvalent antiserum and 34.0% who have used it. Northern Cape doctors administer it correctly more frequently. Only a quarter of respondents knew that polyvalent antiserum can be used after the expiry date. Conclusion: The knowledge and treatment of snake bites by general practitioners must be addressed through more emphasis in undergraduate training and continuing medical education. SA Fam Pract 2004;46(9): 31-34 Article full text in Afrikaans
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".