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Record W4390940302 · doi:10.1080/07399332.2024.2304110

The knowledge domain and emerging trends in the infertility field: A 67-year retrospective study

2024· article· en· W4390940302 on OpenAlexaboutno aff
Razieh Akbari, Zahra Panahi, Marjan Ghaemi, Sedigheh Hantoushzadeh

Bibliographic record

VenueHealth Care For Women International · 2024
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInfertilityEndometriosisFertilityGynecologyMedicinePolycystic ovaryFemale infertilityChildlessnessMale infertilityAssisted reproductive technologyObstetricsPopulationPregnancyBiologyObesityInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Infertility is a significant problem influencing many couples. Our purpose was to assess the field of infertility in Obstetrics and Gynecology from 1955 to 2022 reviewing 3575 documents found in the Web of Science database. Most articles were in the areas of Reproductive Biology, Fertility, Endometriosis & Hysterectomy, and Chromosome Disorders. We found publication has increased dramatically since 1989. Agarwal, Thomas, and Sharma; United States, England, and Canada; Fertility and Sterility, Human Reproduction, and AJOG were the most-cited authors, countries, and journals, respectively. We discovered five substantive clusters: male infertility factors, female infertility factors, causes and treatment of infertility, the consequence of infertility, and assisted reproductive techniques. Using bibliometric review (Co-citation analysis) six research areas were found: semen analysis and sperm morphology, regional differences in the psychological effects of infertility, unexplained infertility, endometriosis, diagnosis and treatment of infertility, and polycystic ovary syndrome. Despite advances in understanding infertility, further research is needed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.397
Teacher spread0.378 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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