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Record W3016668438 · doi:10.1701/3347.33181

Pandemie post-normali. Perché CoViD-19 richiede un nuovo approccio alla scienza

2020· article· en· W3016668438 on OpenAlexaff
David Waltner‐Toews, Annibale Biggeri, Bruna De Marchi, Silvio Funtowicz, Mario Giampietro, Martin O’Connor, Jerome R. Ravetz, Andrea Saltelli, J.P. van der Sluijs

Bibliographic record

VenueRecenti Progressi in Medicina · 2020
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of ReginaUniversity of Guelph
FundersEconomic and Social Research Council
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Covenant2019-20 coronavirus outbreakNew normalSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Falling (accident)VirologyHealth scienceCoronavirus InfectionsPolitical scienceMedicineLawInfectious disease (medical specialty)Medical educationEnvironmental healthDisease

Abstract

fetched live from OpenAlex

In addressing pandemics, science has never seemed more needed and useful, while at the same time limited and powerless. The existing contract between science and society is falling apart. A new covenant is urgently needed to navigate the days ahead.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.996
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0440.013

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 head0.225
GPT teacher head0.460
Teacher spread0.235 · 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.

Study designTheoretical or conceptual
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

Citations37
Published2020
Admission routes1
Has abstractyes

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