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Record W4220874493 · doi:10.1038/s41431-022-01075-0

The 2019 and 2021 International Workshops on Alport Syndrome

2022· article· en· W4220874493 on OpenAlexafffund
Sergio Daga, Jie Ding, Constantinos Deltas, Judy Savige, Beata S. Lipska‐Ziętkiewicz, Julia Hoefele, Frances Flinter, Daniel P. Gale, Marina Aksenova, Hirofumi Kai, Laura Perin, Moumita Barua, Roser Torrá, Jeff H. Miner, Laura Massella, Danica Galešić Ljubanović, Rachel Lennon, André Weinstock, Bertrand Knebelmann, Agnė Čerkauskaitė, Susie Gear, Oliver Groß, Neil Turner, Margherita Baldassarri, Anna Maria Pinto, Alessandra Renieri

Bibliographic record

VenueEuropean Journal of Human Genetics · 2022
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesInstituto de Salud Carlos IIINational Institutes of HealthHrvatska Zaklada za ZnanostEuropean Regional Development FundSanofiEuropean CommissionKidney Foundation of CanadaThird Health ProgrammeAlport Syndrome FoundationUniversità degli Studi di SienaUniversity of CyprusRegione ToscanaEuropean Rare Kidney Disease Reference NetworkResearch and Innovation FoundationUniversity of Southern CaliforniaSveučilište u Zagrebu
KeywordsAlport syndromeDiseaseMedicineGlomerulonephritisFamily medicineGeneticsBiologyInternal medicineKidney

Abstract

fetched live from OpenAlex

In 1927 Arthur Cecil Alport, a South African physician, described a British family with an inherited form of kidney disease that affected males more severely than females and was sometimes associated with hearing loss. In 1961, the eponymous name Alport syndrome was adopted. In the late twentieth century three genes responsible for the disease were discovered: COL4A3, COL4A4, and COL4A5 encoding for the α3, α4, α5 polypeptide chains of type IV collagen, respectively. These chains assemble to form heterotrimers of type IV collagen in the glomerular basement membrane. Scientists, clinicians, patient representatives and their families, and pharma companies attended the 2019 International Workshop on Alport Syndrome, held in Siena, Italy, from October 22 to 26, and the 2021 online Workshop from November 30 to December 4. The main topics included: disease re-naming, acknowledging the need to identify an appropriate term able to reflect considerable clinical variability; a strategy for increasing the molecular diagnostic rate; genotype-phenotype correlation from monogenic to digenic forms; new therapeutics and new therapeutic approaches; and gene therapy using gene editing. The exceptional collaborative climate that was established in the magical medieval setting of Siena continued in the online workshop of 2021. Conditions were established for collaborations between leading experts in the sector, including patients and drug companies, with the aim of identifying a cure for Alport syndrome.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.299
Teacher spread0.274 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations36
Published2022
Admission routes2
Has abstractyes

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