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Record W3015197879 · doi:10.1016/s2215-0366(20)30168-1

Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science

2020· review· en· W3015197879 on OpenAlexfundno aff
Emily A. Holmes, Rory C. O’Connor, V. Hugh Perry, Irene Tracey, Simon Wessely, Louise Arseneault, Clive Ballard, Helen Christensen, Roxane Cohen Silver, Ian Everall, Tamsin Ford, Ann John, Thomas Kabir, Kate King, Ira Madan, Susan Michie, Andrew K Przybylski, Roz Shafran, Angela Sweeney, Carol M. Worthman, Lucy Yardley, Katherine Cowan, Claire Cope, Matthew Hotopf, Edward T. Bullmore

Bibliographic record

VenueThe Lancet Psychiatry · 2020
Typereview
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
FundersMedical Research FoundationJohn Fell Fund, University of OxfordMedical Research CouncilNIHR Maudsley Biomedical Research CentreEconomic and Social Research CouncilUniversity of CambridgeNational Institute for Health Research Southampton Biomedical Research CentreUppsala UniversitetHuo Family FoundationVetenskapsrådetUniversity of GlasgowChief Scientist OfficeKing's College LondonScottish GovernmentLupina FoundationLeverhulme TrustNational Institute for Health and Care ResearchDepartment for Business, Energy and Industrial Strategy, UK GovernmentNHS Health ScotlandAcademy of Medical SciencesMQ: Transforming Mental HealthBritish AcademyOak FoundationNational Science Foundation
KeywordsCoronavirus disease 2019 (COVID-19)PandemicCall to actionMultidisciplinary approach2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mental healthAction (physics)Coronavirus InfectionsBetacoronavirusMEDLINEPsychologyMedicineData sciencePsychiatryVirologyComputer sciencePolitical scienceSociologyBusinessSocial scienceDiseaseInfectious disease (medical specialty)Pathology

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)0.011
metaresearch head score (Gemma)0.018
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 score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.003
Science and technology studies0.0020.004
Scholarly communication0.0050.009
Open science0.0030.007
Research integrity0.0140.018
Insufficient payload (model declined to judge)0.0260.005

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 head0.660
GPT teacher head0.648
Teacher spread0.012 · 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

Citations6,054
Published2020
Admission routes1
Has abstractno

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