Human Energy Field: A Concept Analysis
Bibliographic record
Abstract
The human energy field (HEF) as a phenomenon of interest across disciplines has gained increased attention over the 20th and 21st centuries. However, a concern has arisen that there is a lack of evidence to support the concept of the HEF as a phenomenon of interest to professional nurses and nursing practice. Using Chinn and Kramer's method of creating conceptual meaning, a concept analysis was conducted for the purpose of developing a conceptual definition of HEF. A systematic review of the literature using the CINAHL database yielded a total of 81 articles and text sources that were determined to be relevant to the concept analysis. The HEF is defined as a luminous field of energy that comprises a person, extends beyond the physical body, and is in a continuous mutual process with the environmental energy field. It is a vital energy that is a continuous whole and is recognized by its unique pattern; it is dynamic, creative, nonlinear, unpredictable, and flows in lower and higher frequencies. The balanced HEF is characterized by flow, rhythm, symmetry, and gentle vibration.
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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".