A Dialogue with Dr. Marilyn A. Ray: Nurse Scholar and USAF Veteran
Bibliographic record
Abstract
Dr. Marilyn A. Ray, nurse scholar and retired United States Air Force (USAF) veteran and former flight nurse, began her nursing scholarship in Canada. She was influenced by the experiences and interprofessional scholarly ideas that she encountered along her career trajectory. Her early love of the air and space led her to the United States Air Force Nurse Corps, where she served as a flight nurse during the Vietnam war era, followed by leadership positions in nursing education, administration, practice, and research. Dr. Ray's contributions to nursing knowledge includes two nursing theories and a caring inquiry methodology. Dr. Ray is helping to create a new caring science certificate program at Florida Atlantic University, Christine E. Lynn College of Nursing. In this column, Dr. Ray shares the story of her scholarly influences and how they helped her care for her husband and gain insight into her contributions to nursing knowledge development.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.022 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".