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Record W3082152566 · doi:10.7764/horiz_enferm.28.3.22

Desarrollo sustentable desde el enfoque de autocuidado: un aporte a la práctica de enfermería

2017· article· es· W3082152566 on OpenAlexaboutno aff
María Teresa Urrutia S, Guillermo Arce, Maria Paz Palma

Bibliographic record

VenueHorizonte de enfermeria · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La relacion entre salud y ambiente no es una tematica reciente, ya en el ano 1974 la Agencia de Salud Publica de Canada establece en su informe Lalonde los factores claves que parecian determinar el estado de salud de los individuos, identificando asi el estilo de vida, el ambiente, la biologia humana y los servicios de salud. En el ano 2012, se realiza la Conferencia de las Naciones Unidas sobre el desarrollo sostenible, que en su documento final “El futuro que queremos” senala “la salud es una condicion previa, un resultado y un indicador de las tres dimensiones del desarrollo sostenible”, es decir, las dimensiones social, ambiental y economica. El impacto que tienen los cambios en el ecosistema sobre la salud de la poblacion esta en directa relacion en como el ser humano se relaciona con su entorno y utiliza los recursos disponibles brindandoles la oportunidad de renovarse a traves de ciclos naturales. Es asi como desde el paradigma de sustentabilidad se propone observar, comprender e intervenir en nuestro entorno teniendo presente que todos los sistemas, tanto naturales como los creados por el hombre, interactuan e influyen entre si. A traves de dos de los requisitos de Autocuidado de la salud como son normalidad y peligros para la vida, planteados por Dorothea Orem se analizara como los cambios en nuestro ecosistema pueden repercutir en el continuo salud-enfermedad de las personas.

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)0.022
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.021
Scholarly communication0.0110.008
Open science0.0030.007
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.405
Teacher spread0.366 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes1
Has abstractyes

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