MétaCan
Menu
Back to cohort
Record W3198447292 · doi:10.1016/j.jadr.2021.100213

Anticipating the long-term neurodevelopmental impact of the COVID-19 pandemic on newborns and infants: A call for research and preventive policy

2021· article· en· W3198447292 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Affective Disorders Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsCentre for Addiction and Mental HealthPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPandemicMental healthCoronavirus disease 2019 (COVID-19)MedicineCohort studyEarly childhoodCohortPsychiatryPediatricsPsychologyDevelopmental psychologyDisease

Abstract

fetched live from OpenAlex

It is estimated that 116 million children were born worldwide in the first nine months of the COVID-19 pandemic. Given the critical importance of early life for neurodevelopment, and evidence suggesting that prenatal maternal stress and early childhood adversity negatively impact neurodevelopment, it is alarming that many pregnant women and new mothers are experiencing high levels of pandemic-related stress. Research and proactive mental health policy is needed to minimize the impact of the COVID-19 pandemic on the future mental health of a global cohort of newborns and infants.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.448
Teacher spread0.382 · 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