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Record W2460098962

A look at dialysis delivery in Australia.

2001· article· en· W2460098962 on OpenAlexaff
Blake Pg

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsDialysisDelivery systemPopulationBusinessEconomic growthMedicineHealth care deliveryIncidence (geometry)Development economicsEnvironmental healthEconomicsSurgeryHealth care
DOInot available

Abstract

fetched live from OpenAlex

Australia, in a sense, has as many dialysis delivery systems as it has states, with the differences in delivery systems being far greater between those states than is the case, for example, in the U.S. However, if common trends are apparent across the nation in dialysis delivery, they include: an increasing tendency to move HD delivery out of major teaching hospital centres into the community a modest decrease in PD use as more HD becomes available an increased role for the private sector in terms of HD delivery, ranging from direct facility ownership to pay-per-treatment arrangements in public hospitals an awareness of a need to make particular provision for the Aboriginal population, given their high rate of ESRD, their geographical dispersion, and their socio-economic deprivation. It will be interesting to observe how these processes evolve in the years ahead and whether these initiatives lead to "catch up" in Australia's incidence of treated ESRD relative to that of other Western countries.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.037
GPT teacher head0.252
Teacher spread0.215 · 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 designObservational
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

Citations2
Published2001
Admission routes1
Has abstractyes

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