Tumor imaging instruction and assessment at chiropractic colleges in North America: a pilot study with implications for National Board of Chiropractic Examiners content
Bibliographic record
Abstract
Objective: This pilot study tested a survey instrument pertaining to the instruction and assessment of tumor imaging in chiropractic training programs. The secondary purpose was to gather data regarding credentials of lead instructors, textbook and resource use, and tumors taught and assessed. Methods: An electronic survey was distributed to lead tumor imaging instructors at all chiropractic colleges in the United States and Canada. A focus group of tumor imaging instructors was conducted to clarify ambiguous data. Results: Diplomate status with the American Chiropractic Board of Radiology was held by 87.5% of the instructor respondents. There were similarities in course content and assessment across institutions. A total of 26 tumors were considered clinically significant by more than 65% of instructors, 9 tumors were identified as not clinically significant by more than 65%, and 4 tumors were considered clinically significant by 35% to 65% of instructors. There was correlation between those instructors who evaluated on various tumors and those who feel it is important to evaluate such tumors (rS = 0.94, p < .001). The focus group addressed the 4 equivocal tumors and recommended 3 be added to the list of clinically insignificant tumors. Conclusion: The survey instrument is ready to be used to conduct a study of all clinical areas of the chiropractic curriculum. A total of 12 tumors were recommended for removal from National Board of Chiropractic Examiners tests. The authors recommend that the Academics Committee of the American Chiropractic Board of Radiology share information regarding learning libraries to allow for a richer learning experience across all campuses.
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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".