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An integrative science approach: Value added in stress research

2006· review· en· W2060140004 on OpenAlexaff
Shirley Linda King

Bibliographic record

VenueNursing and Health Sciences · 2006
Typereview
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of AlbertaRoyal College of Physicians and Surgeons of CanadaMount Royal University
Fundersnot available
KeywordsPerspective (graphical)DisciplineValue (mathematics)Field (mathematics)Integrative medicineHealth carePsychologyInterdisciplinarityNursing scienceEngineering ethicsEpistemologySociologyMedicineNursingComputer scienceAlternative medicineSocial sciencePolitical science

Abstract

fetched live from OpenAlex

Integrative approaches to understanding complex health issues can transcend disciplinary and knowledge boundaries and provide opportunities to view phenomena from diverse perspectives. These broad approaches to understanding phenomena of interest to nursing might provide new directions for nursing research and be a requisite for delivering safe, responsible, and holistic nursing care. The relationship between stress and illness is a strong example of a field of study that can be understood more fully from an integrative perspective. The potential of an integrative approach to contribute to improvements in human health and well-being outweigh historical biases that have been associated with an integrative science approach.

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 imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0140.016
Science and technology studies0.0020.017
Scholarly communication0.0120.020
Open science0.0040.010
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.512
GPT teacher head0.685
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2006
Admission routes1
Has abstractyes

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