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The International Quotidian Dialysis Registry: Annual Report 2007

2007· article· en· W4254788595 on OpenAlexaffvenue
Gihad Nesrallah, Rita S. Suri, Shannon T. CARTER, Louise Moist, Amit X. Garg, Christian Awaraji, Robert M. Lindsay

Bibliographic record

VenueHemodialysis International · 2007
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHumber River Regional HospitalLondon Health Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineDialysisCohortHemodialysisPatient registryEmergency medicineFamily medicineMedical emergencyPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

In view of the need to study both intermediate and definitive outcomes associated with daily and extended-hours hemodialysis (HD), our group has undertaken the design and implementation of an international registry to collect data describing the treatments and outcomes of patients treated with these regimens. The International Quotidian Dialysis Registry began recruiting patients in June 2004. There are currently 229 patients enrolled in the registry, up from 199 last year. The projected growth is 2000 patients by 2008. This paper constitutes the third annual report of progress of patient and center recruitment, and includes descriptive data drawn from the 3 primary patient groups currently tracked by the registry: home nocturnal, home short-daily, and in-center short-daily HD. As the cohort grows, patients will be compared with control subjects drawn from their respective national registries, and comparative analyses will follow.

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)0.010
metaresearch head score (Gemma)0.012
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 score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.010
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.007

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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

Citations13
Published2007
Admission routes2
Has abstractyes

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