369 BONE MARROW TRANSPLANTATION IN CHILDREN—SEEN THROUGH THEIR EYES.
Bibliographic record
Abstract
Bone marrow transplantation in children is a time in the trajectory of their therapy characterized by strict isolation from family, friends, and home and accompanied by profound sequelae from chemotherapy, immunocompromise, and pancytopenia. Although isolation is essential to minimize complications, little is known about how these children experience this period of their lives and the impact on mental well-being as they remain isolated. Using the technique of photo voice, pediatric and adolescent patients were given the opportunity to share their bone marrow transplant experience with health care providers and other children embarking on similar therapies. Photo voice is a technique that involves providing patients with a disposable camera with which to give ‘voice’ to and share their treatment experience before, during, and after their transplant. Patients were prompted with specific questions. For example, what do you wish to share with your health care team, your parents, friends, and other children going through the same experience? What was being in isolation like? How did you cope with pain? Once the photographs were developed, the patients were interviewed to explore the significance of each photo and their emotions surrounding the pictures. It is obvious that isolation is an individual experience for each patient and family. However, certain themes developed in the photos, including the importance of family, the health care team, the frustration of watching the world through a window, and the importance of special friends. In the future, the photos will be collated into an audiovisual educational presentation as well as a hard-copy book for children to learn about the experience of BMT and isolation prior to their transplants.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".