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Record W4246886704 · doi:10.1093/ndt/21.suppl_4.iv105

Toxic acute renal failure

2006· article· en· W4246886704 on OpenAlexaff
Kannaiyan S Rabindranath, Alison M. MacLeod, Norman Muirhead, Yang Kim, Kang Sun, Yeong Shik Kim, Jeong-Nyeo Lee, Xinling Liang, Zhiming Ye, Wei Shi, Wenjian Wang, Yanqiang Peng, Jolanta Małyszko, Hanna Bachórzewska-Gajewska, Jacek Małyszko, Krystyna Pawlak, Michał Myśliwiec, Sławomir Dobrzycki, Ulla Häußler, Maik Backes, Frieder Keller, Heshmatollah Shahbazian, Haiat Mombini, Alireza Kharadmand

Bibliographic record

VenueNephrology Dialysis Transplantation · 2006
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineIntensive care medicineHemodialysisInternal medicine

Abstract

fetched live from OpenAlex

Toxic acute renal failure iv105Also there were relationship between level of serum,s Ca with T-Score,s mean of left femoral neck (P-Value=0.031).Conclusions: We foumd great relationship existed between level of serum,s Ca, Alk.P, PTH and duration of hemodialysis with BMD of lumbar and femoral neck in ESRD patients.We recommend measurement of BMD for all patients every year and measurement level of Ca, Alk.P and PTH every 2 months in dialysis patients for diagnosis of high risk patients for enough treatment to prevented.Renal osteodysytrophy should be controlled by this factors to was prevented of morbidity and mortality due to fracture in lumbar and femoral neck regions in ESRD patients. Toxic acute renal failure

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.007
GPT teacher head0.244
Teacher spread0.238 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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