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Record W2052207090 · doi:10.1016/j.nephro.2012.02.004

Les biomarqueurs d’atteinte rénale

2012· review· fr· W2052207090 on OpenAlexaff
Yann Guéguen, Caroline Rouas

Bibliographic record

VenueNéphrologie & Thérapeutique · 2012
Typereview
Languagefr
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineIntensive care medicineKidney diseaseNephrotoxicityDiseaseMechanism (biology)Identification (biology)PathologyKidneyInternal medicineBiology

Abstract

fetched live from OpenAlex

Les pathologies rénales sont actuellement en constante augmentation dans les sociétés occidentales du fait des conditions de vie d’un individu (âge, mode de vie, pathologie chronique, etc.) ou encore de l’exposition potentielle à de nombreuses substances néphrotoxiques. Aujourd’hui, les mécanismes d’atteinte rénale sont de mieux en mieux connus. Néanmoins, le rein étant une structure complexe et multifonctionnelle, la gestion clinique des déficiences rénales (pronostic, diagnostic, mise en place d’une thérapie) reste toujours un problème significatif en clinique. En effet, les paramètres cliniques traditionnels sont peu sensibles et non discriminants et indiquent plutôt une déficience fonctionnelle qu’une altération tissulaire sous-jacente. Dans ce contexte, l’identification et le développement de nouveaux biomarqueurs d’atteinte rénale entrepris depuis quelques années devraient permettre une identification de manière plus précoce, plus spécifique et plus sensible des insuffisances rénales aiguës ou chroniques en clinique et ainsi une meilleure appréhension de la prise en charge clinique de ces déficiences rénales. Over the last few decades, prevalence of renal diseases has grown continuously in occidental societies due to life conditions (age, life style, chronic disease, etc.) or potential exposure to nephrotoxic agents (drugs and environmental chemicals). Today, the knowledge of the nephropatology mechanism is improving. Nevertheless, considering it is a complex and multifunctional structure, the clinical strategy of this issue (prognostic, diagnostic or therapy) keeps posing a major challenge for clinicians mostly because classical markers are not sensitive enough and require hours before reaching significant levels. Furthermore, most of these markers provide information on function and not on structural integrity of the tissue. Identification and development of new biomarkers share promise of improvement in the rapid diagnostic of kidney diseases and development of new cures in order to optimize the clinical strategy associated to the 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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.012

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 head0.123
GPT teacher head0.376
Teacher spread0.253 · 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
GenreReview

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

Citations11
Published2012
Admission routes1
Has abstractyes

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