MétaCan
Menu
Back to cohort
Record W227659081 · doi:10.1093/pch/11.5.283

Follow-up issues with multiples

2006· article· en· W227659081 on OpenAlexaff
Aideen M. Moore, Karel O’Brien

Bibliographic record

VenuePaediatrics & Child Health · 2006
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicineIntrauterine growth restrictionCerebral palsyPregnancyLow birth weightObstetricsPediatricsBirth weightFetusPsychiatry

Abstract

fetched live from OpenAlex

The rate of multiple pregnancy has increased in developed countries, a finding usually attributed to more widespread use of assisted reproductive technologies. Multiple pregnancies are associated with a greater risk of pregnancy complications, including intrauterine growth restriction of one or more of the fetuses, vascular communications within a shared monochorionic placenta and premature delivery. Surviving infants are at significantly greater risk of developing cerebral palsy due to a combination of a higher proportion of them being preterm or of low birth weight, and complications associated with chorionicity. These infants are also at greater risk for abnormal cognitive development and learning disabilities for the same reasons. Parenting styles and family dynamics may also differ with multiples compared with singletons, which may affect long-term behaviour and development.Thus, infants of multiple pregnancies should receive careful neurodevelopmental follow-up. For larger, lower risk infants, this follow-up may be provided by general paediatricians within the community. However, for infants with birth weights of less than 1000 g or with a complicated antenatal or neonatal course, follow-up should be in a high-risk neonatal follow-up clinic with appropriate multidisciplinary support.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.392
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicAssisted Reproductive Technology and Twin PregnancyFrench-language works237,207