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Record W2116713679 · doi:10.1586/17474108.3.5.627

Will<i>in vitro</i>maturation ever be used in all IVF patients?

2008· article· en· W2116713679 on OpenAlexaff
Ezgi Demirtaş, Hananel Holzer, Weon‐Young Son, Shai E. Elizur, Dan Levin, Ri‐Cheng Chian, Seang Lin Tan

Bibliographic record

VenueExpert Review of Obstetrics & Gynecology · 2008
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsIn vitro fertilisationOvarian hyperstimulation syndromeMedicineIn vitro maturationAndrologyPregnancyIn vitroAssisted reproductive technologyGynecologyPregnancy rateControlled ovarian hyperstimulationObstetricsInfertilityEmbryoOocyteBiologyCell biology

Abstract

fetched live from OpenAlex

In vitro maturation of human oocytes obtained from unstimulated ovaries offers a more ‘patient friendly’ treatment option than conventional IVF treatment with ovarian stimulation to the couples undergoing assisted reproductive technologies. It has classically been offered to women who are considered high risk for ovarian hyperstimulation syndrome. Since significant progress has been made to improve the implantation and pregnancy rates using in vitro matured oocytes, the patient spectrum for in vitro maturation treatment has become wider. However, implantation and pregnancy rates of conventional IVF are still higher than those of unstimulated cycles followed by in vitro maturation. To improve the in vitro maturation outcomes, some studies have focused on improving in vitro culture conditions, whereas others have tried to improve the quality and quantity of oocytes retrieved by modifications in the follow-up of treatment cycles.

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)0.003
metaresearch head score (Gemma)0.008
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: Commentary · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.042
GPT teacher head0.326
Teacher spread0.285 · 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
GenreCommentary

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

Citations2
Published2008
Admission routes1
Has abstractyes

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