72 J Can Chiropr Assoc 2007; 51(2) Commentary Case reports: an important contribution to chiropractic literature
Bibliographic record
Abstract
How many of you have treated these conditions? Sciatica, mechanical low back pain, headache, thoracic outlet syndrome, neck pain, costo-vertebral pain, whip-lash, TMJ, shoulder pain, hip pain, knee pain.... The list could go on and on but you get the point. As chiropractors, we treat these conditions every day. Not everyone knows this. Neither do other professionals, nor the scientific community, understand what chiropractors do. This is because, as chiropractors, we keep it a secret and do not write about our successes. If every chiroprac-tor in Canada would write about a case that they have successfully treated, we would add approximately 10,000 articles to the library pool of scientific literature. Chiropractors appear to have a form of apathy, not nec-essarily apathy toward their practice nor patients but to-
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 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) | 0.000 | 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".