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Record W2162463240 · doi:10.1002/cncr.22106

Choice in fertility preservation in girls and adolescent women with cancer

2006· review· en· W2162463240 on OpenAlexaff
Jeffrey A. Nisker, Fran�oise Baylis, Carolyn McLeod

Bibliographic record

VenueCancer · 2006
Typereview
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsDalhousie UniversityWestern University
Fundersnot available
KeywordsFertility preservationMedicineInfertilityFertilityEndometrial cancerUterusGynecologyIn vitro fertilisationObstetricsCancerPregnancyInternal medicinePopulation

Abstract

fetched live from OpenAlex

With the cure rate for many pediatric malignancies now between 70% and 90%, infertility becomes an increasingly important issue. Strategies for preserving fertility in girls and adolescent women occur in two distinct phases. The first phase includes oophorectomy (usually unilateral) and cryopreservation of ovarian cortex slices or individual oocytes; ultrasound-guided needle aspiration of oocytes, with or without in vitro maturation (IVM), followed by cryopreservation; and ovarian autografting to a distant site. The second phase occurs if the woman chooses to pursue pregnancy, and includes IVM of the oocytes, followed by in vitro fertilization (IVF) and transfer of any created embryos to the woman's uterus (or to a surrogate's uterus if the cancer patient's uterus has been surgically removed or the endometrium destroyed by radiotherapy). For ovarian autografting, the woman would undergo menotropin ovarian stimulation and retrieval of matured oocytes (likely by laparotomy, but possibly by ultrasound-guided needle aspiration if the ovary is positioned in an inaccessible location). The ethical challenges with each of these phases are many of fertility preservation and include issues of informed choice (consent or refusal). The lack of proven benefit with these strategies and the associated potential physical and psychological harms require careful attention to the key elements of informed choice, which include decisional capacity, disclosure, understanding and voluntariness, and to the benefits of in-depth counseling to promote free and informed choice at a time that is emotionally difficult for the decision makers.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.099
GPT teacher head0.416
Teacher spread0.317 · 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

Citations38
Published2006
Admission routes1
Has abstractyes

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