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Record W3020249661 · doi:10.1016/j.bbih.2020.100076

Three insights on psychoneuroimmunology of mood disorders to be taken from the COVID-19 pandemic

2020· review· en· W3020249661 on OpenAlexafffund
Elisa Brietzke, Taylor Magee, Rafael C. Freire, Fabiano A. Gomes, Roumen Milev

Bibliographic record

VenueBrain Behavior & Immunity - Health · 2020
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsProvidence Health CareKingston Health Sciences CentreQueen's University
FundersQueen's University
KeywordsPandemicCoronavirus disease 2019 (COVID-19)MoodPsychoneuroimmunologySurprise2019-20 coronavirus outbreakMood disordersSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PsychologyCoronavirusOutbreakPsychiatryMedicineVirologyAnxietyDiseaseSocial psychologyImmunologyInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

In the recent months, the world was taken by surprise by the outbreak of a coronavirus (SARS-CoV-2) pandemic (COVID-19). The COVID-19 pandemic is a unique opportunity to advance the understanding of the association of respiratory viruses with mood disorders and suicide. In this editorial, we explore three insights to the neuropsychoneuroimmunology of mood disorders that could be taken from the COVID-19 pandemic.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.236
GPT teacher head0.417
Teacher spread0.181 · 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

Citations22
Published2020
Admission routes2
Has abstractyes

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Same venueBrain Behavior & Immunity - HealthSame topicTryptophan and brain disordersFrench-language works237,207