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Record W3031774656 · doi:10.1007/s40620-020-00756-7

Nothing will ever be as before. Reflections on the COVID-19 epidemics by nephrologists in eleven countries

2020· editorial· en· W3031774656 on OpenAlexfundno aff
Giovanni Gambaro, Giorgina Barbara Piccoli

Bibliographic record

VenueJournal of Nephrology · 2020
Typeeditorial
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
FundersInstituto de Seguriidad y Servicios Sociales de los Trabadores del EstadoUniversitätsspital ZürichUniversità degli Studi di VeronaRoyal Adelaide HospitalUniversité Laval
KeywordsCoronavirus disease 2019 (COVID-19)NothingSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakCoronavirus InfectionsPandemicVirologyBetacoronavirusMedicinePhilosophyInternal medicineEpistemologyOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

It is difficult to define the COVID-19 epidemics: it is the black swan challenging what we thought we knew, confronting countries with a high level of technology with problems that seemed to belong to the past. It is a disaster foretold, predicted by prophetic writers and enlightened politicians; it is the fraudulent mistake that has put everyone in the world at risk However we see it, this epidemic is also a lifechanging experience for patients and physicians

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)0.003
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0000.000

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 head0.086
GPT teacher head0.436
Teacher spread0.350 · 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
GenreCommentary

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

Citations5
Published2020
Admission routes1
Has abstractyes

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