Nursing consultation during home care for cancer patients: scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: to identify and synthesize as scientific evidence about nursing consultation during home care to patients undergoing cancer treatment. Question formulation P (Population) - patients undergoing cancer treatment C (Concept) - data for nursing research and care management. C (Context) - home nursing consultation. What data are relevant for nursing research in the context of home nursing care as people with malignancy? What are the main conducts for the management of nursing care, necessary during a home consultation with cancer patients? Research will be included; published in full in English, Spanish and Portuguese; that deal with care during the nursing home consultation for patients with malignant neoplasms, with a time limit from May 2013 (justification: after the publication in Brazil of the National Policy for the Prevention and Control of Cancer in the Health Care Network of People with Chronic Diseases within the scope of the Unified Health System - SUS). The following will be excluded: editorials, experience reports, theoretical essays, a single case study. Definition of search strategies and databases Databases: 1. PubMed 2. CINAHL 3. Web of Science 4. Scopus 5. LILACS Cochrane Gray literature search: Portal de Teses e Dissertações da CAPES DART-Europe E-Theses Portal Electronic Theses Online Service (EThOS) Repositório Científico de Acesso Aberto de Portugal (RCAAP) National ETD Portal Theses Canada Portal de Tesis Latino americanas World Cat Dissertations and Theses The title and summary of all identified studies will be evaluated, based on the established inclusion and exclusion criteria. Those selected will be evaluated in full for later data extraction.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.049 | 0.035 |
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 it