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Record W7133050273

Influence of satellite dialysis units on utilization and modality selection

2006· dissertation· W7133050273 on OpenAlexaboutno aff
Suma Prakash

Bibliographic record

VenueTSpace · 2006
Typedissertation
Language
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsHemodialysisDialysisHome hemodialysisSatelliteModality (human–computer interaction)Renal replacement therapy
DOInot available

Abstract

fetched live from OpenAlex

This study aimed to determine the effect of constructing satellite hemodialysis units on local rates of renal replacement therapy (RRT) with a retrospective cross sectional design. Dialysis service areas were constructed by assigning patients to geographic regions based on where patients received hemodialysis. Regions served by dialysis units built before and after 1995 comprised the control group exposure groups respectively. The standardized change in rate of RRT between 1995 and 2002 was calculated for both groups. The means of the rates were compared with a t-test. The mean increases in dialysis rates between 1995 and 2002 for the control and exposure groups were 4.01 and 4.36 per 10,000 people respectively (p=0.8). Areas of Ontario without initial local hemodialysis access showed a trend towards being underserved but his was not statistically significant. The implementation of satellite hemodialysis units did not increase local utilization of hemodialysis beyond the baseline rate.

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)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
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 head0.027
GPT teacher head0.330
Teacher spread0.303 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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