MétaCan
Menu
Back to cohort
Record W1498594959 · doi:10.24095/hpcdp.30.4.03

The public health implications of assisted reproductive technologies

2010· article· en· W1498594959 on OpenAlexaffvenue
Raywat Deonandan

Bibliographic record

VenueChronic diseases and injuries in Canada · 2010
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPublic healthAssisted reproductive technologyMedicineReproductive healthQualitative researchPublic relationsOffspringPolitical scienceFamily medicineEnvironmental healthPsychologyNursingSociologyPopulationSocial sciencePregnancyBiologyInfertility

Abstract

fetched live from OpenAlex

OBJECTIVE: The public health implications of Assisted Reproductive Technologies (ART) are largely unknown by researchers and policy makers alike. Outcomes need to be considered, not just as clinical issues, but in terms of effect on public health. METHODS: Using a qualitative key informant process involving interviews with selected professionals and a review of the medical literature, eight general themes of public health issues associated with ART were identified, and are discussed. RECOMMENDATIONS: Short and long-term health outcomes of women undergoing ART procedures, and of their offspring, need to be considered, as do the epidemiological risks associated with donated gametes and the effect on health services of multiple and preterm births, both produced in higher rates by ART. A national surveillance system and greater inter-jurisdictional communication are important strategies for addressing these evolving concerns.

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)0.007
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.009
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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

Citations10
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueChronic diseases and injuries in CanadaSame topicAssisted Reproductive Technology and Twin PregnancyFrench-language works237,207