Bibliographic record
Abstract
Gerontological nursing is a unique area of nursing. The cornerstone of the gerontological nursing process is assessment. In some traditional education models, nurses are taught assessments in general areas, such as cardiology, neurology, urology, and orthopedics. Little emphasis is placed on integrating these systems. A one-day workshop was developed with the objective to further develop the assessment skills of the registered nurse (RN) in continuing care by demonstrating a holistic approach to assessment and care planning. For this workshop, the "giants of geriatric medicine," namely falls, incontinence, confusion, iatrogenic illness, and impaired homeostasis (Cape, 1978) were further developed into a geriatric nursing model to include the psychosocial issues. This model demonstrates a way of assessing and integrating the information known about the resident. To ensure the workshop content was practical for the nurse, existing resident care documentation within the sponsoring organization, The Capital Care Group, was used. Through the education provided in the workshop, the RNs recognized that individualized care is based on full assessment of the resident, integration of the information gathered, and complete documentation.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
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".