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Record W3113578509 · doi:10.29289/25945394202020200052

Complex fibroadenoma: bibliometric literature review and presentation of a clinical case

2020· article· en· W3113578509 on OpenAlexaff
Ana Beatriz Aguiar Cardoso, G Schröder, Polyanna Zimermann, Thiago Santos Lima Almendra, Antonione Santos Bezerra Pinto

Bibliographic record

VenueMastology · 2020
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsFibroadenomaMedicineWeb of sciencePathologicalPopulationBreast cancerPathologyPresentation (obstetrics)ApocrineStromal cellCancerInternal medicineRadiologyMeta-analysis

Abstract

fetched live from OpenAlex

Fibroadenomas (FAs) are benign fibro-epithelial tumours of the breast characterized by being biphasic and having stromal and epithelial components. It is estimated that FAs affect more than 20 percent of the general population aged 16–40 years old. Complex FAs are a sub-type of fibroadenoma presenting one or more pathological characteristics, such as epithelial calcifications, apocrine metaplasias, sclerosing adenoma and cysts larger than 3 mm. According to studies elsewhere, women with complex FAs are 3.1 times more likely to develop breast cancer. The objective of the present study was to map the scientific production of articles on complex FA in the international literature. The ISI Web of Knowledge (Web of Science), one of the main scientific databases in the world, was searched with the following terms: (“complex” and “fibroadenoma”) or (“fibroadenoma” and “complex”). Only articles published between 1981 and 2019 were considered for a bibliometric review, in which 160 articles from 126 different periodicals were identified after using refinement filters. Moreover, a clinical case was also discussed based on the patient’s medical record and interview.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.1340.112
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.125
GPT teacher head0.405
Teacher spread0.280 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
Domainnot available
GenreEmpirical · Review

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

Citations1
Published2020
Admission routes1
Has abstractyes

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