Bibliographic record
Abstract
James Giordano states that “taken together, these factors” (lack of evidence of superiority of cervical manipulation and absence of a definable at-risk group) “should strongly weigh the disposition of clinicians toward their use of cervical manipulation.” I think “toward” should be replaced with “against” in this sentence. Otherwise, I very much agree with what Giordano writes. In my opinion, ignoring the principles of evidence-based medicine will be detrimental not only to patients but, in the long run, also to chiropractic itself. In my experience, chiropractors tend to take on board scientific evidence only when it is in favor of their practice and ignore it when it is not. I applaud Giordano's view that ethical decision-making must be based on the best evidence available at any given time. My applause gets even louder when Giordano reminds us that the responsibility for getting this message across and building the foundations for this approach lies squarely with the institutions that regulate and teach chiropractic.
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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.028 | 0.021 |
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".