MétaCan
Menu
Back to cohort
Record W2063243137 · doi:10.1586/14737140.7.6.811

Effect of cancer and cancer treatment on human reproduction

2007· review· en· W2063243137 on OpenAlexaff
Mohamed FM Mitwally

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2007
Typereview
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsAmerican Water (Canada)
Fundersnot available
KeywordsMedicineCancerOffspringHuman reproductionAdverse effectReproductionCancer treatmentPregnancyOvarian cancerIntensive care medicineInternal medicineBiology

Abstract

fetched live from OpenAlex

Cancer affecting children and individuals of reproductive age is associated with dilemmas concerning the ability to have a child and whether this child will be healthy. This is particularly true in light of the recent advances in the early detection of cancer and its effective treatment, which has improved survival rates. Both the cancer itself and its treatment have tremendous adverse effects on human reproduction and may result in the complete termination of reproductive ability both in men and women. Even in situations when conception is successfully achieved following cancer diagnosis and treatment, there are concerns regarding the potential increased risk of adverse obstetric and perinatal outcomes. This is especially true when pregnancy occurs shortly after cancer treatment. Moreover, there is a potential risk of chromosomal abnormalities and malformations in the offspring due to possible genetic defects in the germ cells induced by chemotherapy and radiotherapy. In addition, there is (at least theoretically) an increased risk of cancer developing in the offspring, particularly with hereditary cancer syndromes. A multidisciplinary team aware of the possible consequences of cancer treatment on reproduction is very much needed to provide optimal care for these patients after proper counseling regarding the potential adverse effects of cancer treatment on reproduction.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.106
GPT teacher head0.507
Teacher spread0.401 · 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.

Study designOther design
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

Citations17
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueExpert Review of Anticancer TherapySame topicReproductive Biology and FertilityFrench-language works237,207