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Record W2147361061 · doi:10.1093/humrep/deg361

Safety issues in assisted reproductive technology: Aetiology of health problems in singleton ART babies

2003· review· en· W2147361061 on OpenAlexafffund
Raymond Lambert

Bibliographic record

VenueHuman Reproduction · 2003
Typereview
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsSingletonAssisted reproductive technologyMedicineEtiologyObstetricsPregnancyGynecologyBiologyInfertilityPsychiatry

Abstract

fetched live from OpenAlex

The frequency of health problems in singleton assisted reproductive technologies (ART) babies is higher than in singletons from spontaneous gestations. Any of the following factors may be involved: in-vitro technology, ovarian stimulatory drugs and infertility itself. A literature review on premature birth, low birth weight, perinatal mortality and major birth defects in children conceived from infertility treatments was conducted. Only publications comparing the outcome of pregnancy in an infertile group of patients to a matched control group were selected. The analysis of the outcome of singleton pregnancies resulting from IVF versus artificial insemination, obtained with or without the use of ovarian stimulatory agents and obtained with or without the use of a semen donor, suggests that female infertility is an important risk factor. Criteria for screening at-risk infertile women have not yet been identified. Prospective studies designed to identify precisely the aetiology of health problems in singletons ART babies will have to be conducted. The absence of criteria correlating at-risk infertile women to health problems in their children does not allow a gynaecologist the opportunity to offer infertility treatments to the least susceptible patients.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.078
GPT teacher head0.379
Teacher spread0.301 · 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 designSystematic review
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

Citations82
Published2003
Admission routes2
Has abstractyes

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