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Record W2132107385 · doi:10.1093/europace/eut139

What costs matter? Rethinking social costs of new device technologies

2013· letter· en· W2132107385 on OpenAlexaff
Alexandra A. Choby, Alexander M. Clark

Bibliographic record

VenueEP Europace · 2013
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineProductivitySocial costIndirect costsEconomic costBalance (ability)Product (mathematics)Cost driverEconomic growthAccountingEconomics

Abstract

fetched live from OpenAlex

This editorial refers to ‘Cost-of-illness study of patients subjected to cardiac rhythm management devices implantation: results from a single tertiary centre’ by J. Fanourgiakis et al. , 15: 366–375. Costs worthy of consideration often do not make it to the picture in cost-of-illness studies. Thus, there is cause for concern when Fanourgiakis et al .'s1 timely analysis of costs associated with implantable cardioverter-defibrillator (ICD) uptake in Greece estimate social cost only as impact on health resources and lost productivity. Cost-of-illness studies have been critiqued for misevaluation of cost from the patients' perspective, yet beyond this, they fail to capture non-economic costs to society, which however may be a by-product of the economic system. In the USA, for example, rapid adoption of a new technology also may have costs for the evidence base, an outcome that results from industry-driven device regulation. The US regulatory structure struggles to balance innovation with public safety, a practice that, as the history of ICD adoption in the USA shows, has given rise to controversy within and beyond the …

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.017

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 head0.309
GPT teacher head0.401
Teacher spread0.092 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2013
Admission routes1
Has abstractyes

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