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Record W1974559459 · doi:10.1109/iembs.2008.4650212

Survey of clinical engineering effectiveness in developing world hospitals: Equipment resources, procurement and donations

2008· article· en· W1974559459 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsCarleton University
Fundersnot available
KeywordsProcurementDeveloping countryClinical engineeringLatin AmericansDonationBusinessMiddle EastOperations managementEngineering managementEconomic growthEngineeringMarketingHealth careGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This paper presents preliminary findings of a study of clinical engineering effectiveness within developing world hospitals. To date, 169 responses have been collected from 43 countries, primarily from Africa, Latin America and Asia, with some representation from the Middle East and Eastern Europe as well. Data is presented on: 1) hospital and clinical engineering department profiles; 2) human and equipment resources; and 3) equipment procurement and donation processes, with a focus on the role of the clinical engineering department. This is the first study to collect and analyze data on the complexity and state of hospital equipment across the developing world; additionally it is the first to collect significant responses from Africa. Prior to this study, only 10 developing countries had been profiled in international studies.

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 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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.314
GPT teacher head0.512
Teacher spread0.198 · 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

Quick stats

Citations17
Published2008
Admission routes1
Has abstractyes

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