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Record W4387675488 · doi:10.1016/j.cell.2023.09.013

Serotonin reduction in post-acute sequelae of viral infection

2023· article· en· W4387675488 on OpenAlexfundno aff
Andrea C. Wong, Ashwarya S. Devason, Iboro C. Umana, Timothy Cox, Lenka Dohnalová, Lev Litichevskiy, Jonathan Perla, Patrick Lundgren, Zienab Etwebi, Luke Izzo, Jihee Kim, Monika Tetlak, Hélène C. Descamps, Simone L. Park, Stephen Wisser, Aaron D. McKnight, Ryan D. Pardy, Junwon Kim, Niklas Blank, Shaan Patel, Katharina Thum, Sydney Mason, Jean‐Christophe Beltra, Michaël F. Michieletto, Shin Foong Ngiow, Brittany Miller, Megan J. Liou, Bhoomi Madhu, Oxana Dmitrieva-Posocco, Alex S. Huber, Peter Hewins, Christopher Petucci, Candice P. Chu, Gwen Baraniecki‐Zwil, Leila B. Giron, Amy E. Baxter, Allison R. Greenplate, Charlotte Kearns, Kathleen T. Montone, Leslie A. Litzky, Michael D. Feldman, Jorge Henao‐Mejia, Boris Striepen, Holly Ramage, Kellie A. Jurado, Kathryn E. Wellen, Una O’Doherty, Mohamed Abdel‐Mohsen, Alan Landay, Ali Keshavarzian, Timothy J. Henrich, Steven G. Deeks, Michael J. Peluso, Nuala J. Meyer, E. John Wherry, Benjamin Abramoff, Sara Cherry, Christoph A. Thaiss, Maayan Levy

Bibliographic record

VenueCell · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesCenter of Excellence in Environmental Toxicology, University of PennsylvaniaNational Cancer InstituteNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institute on Alcohol Abuse and AlcoholismFonds de Recherche du Québec - SantéPenn Skin Biology and Diseases Resource-based Center, University of PennsylvaniaPenn Center for Precision Medicine, University of PennsylvaniaInfectious Diseases Society of AmericaInstitute on Aging, University of PennsylvaniaBoehringer Ingelheim FondsIDSA FoundationDiabetes Research CenterCanadian Institutes of Health ResearchParker Institute for Cancer ImmunotherapyKenneth Rainin FoundationSearle Scholars ProgramPrevent Cancer FoundationAbramson Cancer CenterEdward Mallinckrodt, Jr. FoundationUniversity of PennsylvaniaNational Institutes of HealthUniversity of FloridaEge University Research FoundationBurroughs Wellcome FundMcKnight FoundationNational Health and Medical Research CouncilCancer Research InstituteAstraZenecaHartwell FoundationAmerican Cancer SocietyInternational Society of BiomechanicsNational Institute of Environmental Health SciencesW. W. Smith Charitable Trust
KeywordsBiologyVirologySerotoninImmunologyGeneticsReceptor

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.011
GPT teacher head0.295
Teacher spread0.284 · 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

Citations361
Published2023
Admission routes1
Has abstractno

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