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Record W7075605877

Aplicación de Lean Manufacturing en el sector sanitario.: Un análisis bibliométrico

2025· article· en· W7075605877 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionFusible alloyArticular cartilage damageDiafiltrationDysgeusiaGestational period
DOInot available

Abstract

fetched live from OpenAlex

The present research performs a bibliometric exercise of the literature on Lean Manufacturing applied in the health sector. For this purpose, the systematic review method proposed by Denyer and Tranfield (2009) is used, which consists of identifying and formulating the research question, locating the literature, selection criteria and evaluation of the studies, analyzing and synthesizing the information, presentation and reporting of the research results in a study timeline of no more than 10 years. Databases such as PubMed for scientific articles and Google Scholar for books were considered. This database was used because the research is a pioneer in the study of the phenomenon and therefore, free access to information through both databases guaranteed access, development and analysis of the scientific production. The results of the bibliometric analysis established a total of 298 articles in PubMed and 46 books in Google Scholar, analyzed according to three criteria: number of articles and books published per year, country of origin and type of document. A growth trend was shown in research on Lean Manufacturing located in the United States, Canada and the United Kingdom. On the other hand, the research revealed that Lean manufacturing is not limited only to the industrial sector, as research in the health area was identified.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.233
Teacher spread0.230 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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