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Record W3013401971 · doi:10.1002/9781119434016.ch18

Sustainable Healthcare Systems

2020· other· en· W3013401971 on OpenAlexaff
Carlos S. Osorio‐González, Krishnamoorthy Hegde, Satinder Kaur Brar, Antonio Avalos Ramírez

Bibliographic record

VenueSustainability · 2020
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCentre National en Électrochimie et en Technologies EnvironnementalesYork UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsSustainabilityHealthcare systemHealth careBusinessWorld populationQuality (philosophy)Healthcare servicePopulationSustainable developmentKey (lock)Risk analysis (engineering)Computer scienceEconomic growthMedicineComputer securityPolitical scienceEconomicsEnvironmental health

Abstract

fetched live from OpenAlex

Healthcare systems around the world are currently undergoing major changes in public policies to offer a better health service to their population. However, some of these systems or models are not entirely inclusive and present discrepancies that directly affect the people who use the system. One of the biggest problems that currently affects healthcare systems is that they are unsustainable (environmentally, socially and economically). Hence, it is imperative to look for a more sustainable system and, to this end, we have opted for the use of sustainable principles to improve the quality of healthcare systems around the world. This chapter shows the key health models that are offered around the world, as well as providing a perspective on the role played by sustainability within these healthcare systems today.

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)0.004
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0090.007
Open science0.0010.007
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0330.009

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 head0.187
GPT teacher head0.416
Teacher spread0.229 · 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
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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