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Record W951525417 · doi:10.1017/cbo9780511730207

Fertility Cryopreservation

2010· book· en· W951525417 on OpenAlexaff
Ri‐Cheng Chian, Amir Arav, Patrick Quinn, Magosaburo Kasai and, Jason E. Swain, Fady Shehata, Zheng Li, Peter Chan, Ariel Revel, David H. Edgar, Barry Behr, Yunxia Cao, Yoshiharu Morimoto, Pierre Vanderzwalmen, Andrea Borini, Jack Y.J. Huang, Evgenia Isachenko, Elkin Lucena

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsMcGill University
Fundersnot available
KeywordsFertility preservationFertilityCryobiologyInfertilityCryopreservationMedicineReproductive medicineOocyte cryopreservationAssisted reproductive technologyGynecologyIntensive care medicineReading (process)Family medicineMedical educationBiologyPopulationPolitical scienceEnvironmental healthPregnancy

Abstract

fetched live from OpenAlex

Protecting the reproductive potential of young patients undergoing cancer therapy is increasingly important. With modern treatment protocols, 80% of patients can be expected to survive. It has been estimated that up to one in 250 young adults will be a survivor of childhood cancer in the future; infertility, however, may be a consequence. As a wide range of fertility preservation methods are increasingly offered by clinicians, this systematic and comprehensive textbook dealing with the cryobiology, technology and clinical approach to this therapy will be essential reading to infertility specialists, embryologists, oncologists, cryobiologists, ObGyns, andrologists, and urologists with an interest in fertility preservation. Fertility Cryopreservation reviews all the techniques of this increasingly important field within reproductive medicine. It covers the basic principles of pertinent cryobiology, and contains major sections on the different therapies available, written by international specialists combining experience from both academic centers and commercial industries.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.234
Teacher spread0.204 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations55
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicReproductive Biology and FertilityFrench-language works237,207