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Record W4237417261 · doi:10.1038/s41380-019-0403-7

Correction: Acute transient cognitive dysfunction and acute brain injury induced by systemic inflammation occur by dissociable IL-1-dependent mechanisms

2019· erratum· en· W4237417261 on OpenAlexaff
Donal Skelly, Éadaoin W. Griffin, Carol Murray, Sarah C. Harney, Conor O’Boyle, Edel Hennessy, Marc‐André Dansereau, Arshed Nazmi, Lucas Silva Tortorelli, J. N. P. Rawlins, David M. Bannerman, Colm Cunningham

Bibliographic record

VenueMolecular Psychiatry · 2019
Typeerratum
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsTrinity College
FundersNational Institute on Aging
KeywordsHippocampal formationSystemic inflammationNeuroscienceEx vivoDepolarizationInflammationIn vivoMedicinePsychologyBiologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Following publication of this article, the authors noticed an error in the abstract, where they incorrectly stated that: “Direct application of IL-1β to ex vivo hippocampal slices induced non-synaptic depolarisation and irreversible loss of membrane potential in CA1 neurons from diseased animals and systemic LPS increased apoptosis in the degenerating brain, in an IL-1RI−/−- dependent fashion”. This has now been corrected to: “Direct application of IL-1β to ex vivo hippocampal slices induced non-synaptic depolarisation and irreversible loss of membrane potential in CA1 neurons from diseased animals and systemic LPS increased apoptosis in the degenerating brain, in an IL-1RI- dependent fashion”. The authors would like to apologise for this error. This has been corrected in both the PDF and HTML versions of the article.

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)0.004
metaresearch head score (Gemma)0.059
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.059
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0510.049

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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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
GenreOther

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

Citations66
Published2019
Admission routes1
Has abstractyes

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