Bibliographic record
Abstract
BACKGROUND AND SIGNIFICANCE: Cancer is the leading cause of death worldwide and accounted for 7.4 million deaths in 2004. By 2030, deaths from cancer have been estimated at 12 million with 30% being preventable. Complementary and alternative medicine remains popular among cancer patients; particularly with chiropractic services. However, the nature of the chiropractic clinical encounter and its reported benefits remains to be fully investigated. Towards these efforts, we begin with a systematic review of the literature on the chiropractic care of patients with cancer. METHODS: The following electronic databases were searched: MANTIS [1965-2010]; Index to Chiropractic Literature [1984-2010]; Pubmed [1966-2010]; Medline [1965-2010] EMBASE [1974-2010], AMED [1975-2010], CINAHL Plus [1965-2010], Alt-Health Watch [1965-2010] and PsychINFO [1965-2010]. Key words used were "cancer" and "neoplasm" in Boolean combination with "chiropractic." Primary investigation/reports in peer-reviewed English journals involving chiropractic care were reviewed. RESULTS: Our review revealed 60 case reports, 2 case series, 21 commentaries, 2 survey studies, and 2 literature reviews. The case reports were diagnostic with commentaries highlighting the importance of recognizing the patient presenting with NMS complaints due to an underlying neoplasm. The chiropractic clinical encounter prior to cancer diagnosis and subsequent medical referral is poorly characterized in the literature. CONCLUSION: Patients with cancer seek the care of chiropractors. The literature does not reflect or describe the totality of the chiropractic clinical encounter. We encourage further research in this field.
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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".