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Record W4316654792 · doi:10.1016/j.neurad.2023.01.005

Cerebral perfusion using ASL in patients with COVID-19 and neurological manifestations: A retrospective multicenter observational study

2023· article· en· W4316654792 on OpenAlexaff
François-Daniel Ardellier, Seyyid Baloglu, Magdalena Sokolska, Vincent Noblet, François Lersy, Olivier Collange, Jean‐Christophe Ferré, Adel Maamar, B. Carsin-Nicol, Julie Helms, Maleka Schenck, Antoine Khalil, Augustin Gaudemer, Sophie Caillard, Julien Pottecher, Nicolas Lefèbvre, Pierre-Emmanuel Zorn, Muriel Matthieu, Jean‐Christophe Brisset, Clotilde Boulay, Véronique Mutschler, Yves Hansmann, Paul‐Michel Mertès, Francis Schneider, Samira Fafi‐Kremer, Mickaël Ohana, Ferhat Meziani, Nicolás Meyer, Tarek Yousry, Mathieu Anheim, François Cotton, Hans Rolf Jäger, Stéphane Kremer, Fabrice Bonneville, G Adam, Guillaume Martin‐Blondel, Jérémie Pariente, Thomas Geeraerts, Hélène Oesterle, Federico Bolognini, Julien Messié, Ghazi Hmeydia, Joseph Benzakoun, Catherine Oppenheim, Jean‐Marc Constans, Serge Metanbou, Adrien Heintz, Blanche Bapst, Imen Megdiche, Lavinia Jager, Patrick Nesser, Yannick Talla, Thomas Tourdias, Juliette Coutureau, Céline Hemmert, Philippe Feuerstein, Nathan Sebag, Sophie Carré, Manel Alleg, Claire Lecocq, Emmanuel Schmitt, René Anxionnat, François Zhu, Géraud Forestier, Aymeric Rouchaud, Pierre‐Olivier Comby, F. Ricolfi, Pierre Thouant, Sylvie Grand, Alexandre Krainik, Isaure de Beaurepaire, Grégoire Bornet, Audrey Lacalm, Patrick Miailhes, Julie Pique, Claire Boutet, Xavier Fabré, Béatrice Claise, Sonia Mirafzal, Laure Calvet, Hubert Desal, Jérôme Berge, Grégoire Boulouis, Apolline Kazémi, Nadya Pyatigorskaya, Augustin Lecler, Suzana Saleme, Myriam Edjlali, Basile Kerleroux, Samir Chenaf

Bibliographic record

VenueJournal of Neuroradiology · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsSte. Anne's Hospital
FundersAgence Nationale de la Recherche
KeywordsMedicinePerfusionFluid-attenuated inversion recoveryRetrospective cohort studyPerfusion scanningCerebral perfusion pressureRadiologyMagnetic resonance imagingTemporal lobeCardiologyInternal medicineNuclear medicineEpilepsy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.353
Teacher spread0.288 · 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

Citations21
Published2023
Admission routes1
Has abstractno

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