Bibliographic record
Abstract
At the time of writing this commentary, knowledge on the pathogenesis of SARS-CoV-2 and how to effectively treat it is lacking. The role of naturopathic treatment approaches or those from the realm of Traditional and Complementary Medicine (T&CM) have received limited attention with respect to their potential role in this pandemic. Based on contemporary research evidence, traditional knowledge and the extensive training and experience of naturopathic doctors (NDs) in pharmacognosy, herbal medicine and clinical nutrition there is reason to believe that naturopathic approaches warrant consideration among the span of possible aids to the global response to COVID-19. Hence, the naturopathic profession undertook the task of conducting rapid reviews to assess the role of specific recommendations in the prevention or treatment of upper respiratory tract infections (URTIs) inclusive of, but not limited to, COVID-19. The focus of all rapid reviews was limited to human studies specific to URTIs either as original research or systematic reviews. With the support of nine naturopathic educational institutions which included a team of over 40 naturopathic researchers, practitioners and content experts from seven countries and five WHO world regions, in two short months the profession has produced ten rapid reviews related to the role of natural health products in treating acute respiratory tract infections, with a further two reviews in draft. These rapid reviews will be published individually and as a dedicated issue of the scientific journal Advances in Integrative Medicine (Elsevier publication). They will be made open-access – meaning they will be free for download. The Task Force was chaired by WNF President Dr Iva Lloyd with Dr Amie Steel and Professor Jon Wardle as research leads. These rapid reviews demonstrate the naturopathic profession’s dedication to evidence-informed decision making and their commitment to being part of the solution to this global pandemic. The following is a brief overview of the findings from the completed reviews.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.003 | 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 teacher head, 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".