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Record W2946948899 · doi:10.1038/s41598-019-44545-0

Publisher Correction: Toxoplasma Modulates Signature Pathways of Human Epilepsy, Neurodegeneration & Cancer

2019· erratum· en· W2946948899 on OpenAlexaff
Huân M. Ngô, Ying Zhou, Hernán Lorenzi, Kai Wang, Taek-Kyun Kim, Yong Zhou, Kamal El Bissati, Ernest Mui, Laura Fraczek, Seesandra V. Rajagopala, Craig W. Roberts, Fiona L. Henriquez, Alexandre Montpetit, Jenefer M. Blackwell, Sarra E. Jamieson, Kelsey M. Wheeler, Ian J. Begeman, Carlos Andrés Naranjo Galvis, Ney Alliey‐Rodriguez, Roderick G. Davis, Liliana Soroceanu, Charles Cobbs, Dennis A. Steindler, Kenneth M. Boyer, A. Gwendolyn Noble, Charles N. Swisher, Peter Heydemann, Peter Rabiah, Shawn Withers, Patricia Soteropoulos, Leroy Hood, Rima McLeod

Bibliographic record

VenueScientific Reports · 2019
Typeerratum
Languageen
FieldImmunology and Microbiology
TopicToxoplasma gondii Research Studies
Canadian institutionsMcGill UniversityMcGill Genome CentreGenome Canada
Fundersnot available
KeywordsNeurodegenerationSignature (topology)EpilepsyComputer scienceComputational biologyNeuroscienceBioinformaticsMedicineBiologyPathologyMathematicsDisease

Abstract

fetched live from OpenAlex

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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)0.002
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.995
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0530.032

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 head0.025
GPT teacher head0.273
Teacher spread0.248 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

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