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Record W3132240972 · doi:10.1038/s41593-020-00783-4

Reactive astrocyte nomenclature, definitions, and future directions

2021· review· en· W3132240972 on OpenAlexaff
Carole Escartin, Elena Galea, András Lakatos, James P. O’Callaghan, Gabor C. Petzold, Alberto Serrano‐Pozo, Christian Steinhäuser, Andrea Volterra, Giorgio Carmignoto, Amit Agarwal, Nicola J. Allen, Alfonso Araque, Luis Barbeito, Ari Barzilai, Dwight E. Bergles, Gilles Bonvento, Arthur M. Butt, Wei-Ting Chen, Martine Cohen‐Salmon, Colm Cunningham, Benjamin Deneen, Bart De Strooper, Blanca Díaz‐Castro, Cinthia Farina, Marc Freeman, Vittorio Gallo, J. E. Goldman, Steven A. Goldman, Magdalena Götz, Antonia Gutiérrez, Philip G. Haydon, Dieter Henrik Heiland, Elly M. Hol, Matthew G. Holt, Masamitsu Iino, Ksenia V. Kastanenka, Helmut Kettenmann, Baljit S. Khakh, Schuichi Koizumi, C. Justin Lee, Shane A. Liddelow, Brian A. MacVicar, Pierre J. Magistretti, Albee Messing, Anusha Mishra, Anna V. Molofsky, Keith K. Murai, Christopher M. Norris, Seiji Okada, Stéphane H. R. Oliet, João Filipe Oliveira, Aude Panatier, Vladimir Parpura, Marcela Pekna, Milos Pekny, Luc Pellerin, Gertrudis Perea, Beatriz Gomez Perez‐Nievas, Frank W. Pfrieger, Kira E. Poskanzer, Francisco J. Quintana, Richard M. Ransohoff, Miriam Riquelme‐Perez, Stefanie Robel, Christine R. Rose, Jeffrey D. Rothstein, Nathalie Rouach, David H. Rowitch, Alexey Semyanov, Swetlana Sirko, Harald Sontheimer, Raymond A. Swanson, Javier Vitórica, I. Wanner, Levi B. Wood, Jiaqian Wu, Binhai Zheng, Eduardo R. Zimmer, Robert Zorec, Michael V. Sofroniew, Alexei Verkhratsky

Bibliographic record

VenueNature Neuroscience · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMcGill University Health CentreUniversity of British Columbia
FundersNational Institute on Drug AbuseNational Institute of Mental HealthMedical Research CouncilCenters for Disease Control and PreventionHorizon 2020 Framework ProgrammeNovo Nordisk FondenNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesGeneralitat de CatalunyaTeva Pharmaceutical IndustriesBundesministerium für Bildung und ForschungNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la RechercheWellcome TrustDeutsche ForschungsgemeinschaftCentre National de la Recherche ScientifiqueNational Institute on AgingAlzheimer's AssociationLundbeckfondenNational Science Foundation
KeywordsNeuroscienceNomenclatureAstrocyteCognitive scienceNeuroscientistPsychologyBiologyZoologyCentral nervous systemTaxonomy (biology)Oligodendrocyte

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0060.007
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.003

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 head0.077
GPT teacher head0.335
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2,366
Published2021
Admission routes1
Has abstractno

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