MétaCan
Menu
Back to cohort
Record W2792007061

Testicular microlithiasis in patients with testicular cancer in the United Kingdom and in Denmark.

2018· article· en· W2792007061 on OpenAlexaff
Malene Roland Vils Pedersen, Catherine Horsfield, Oliver Foot, Jan Lindebjerg, Palle Jørn Sloth Osther, Peter Vedsted, Ashish Chandra, Søren Rafael Rafaelsen, Henrik Møller

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineTesticular cancerGynecologyFamily medicineGeneral surgeryCancerInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Testicular cancer is the most common type of cancer in young Caucasian men. It has been suggested that testicular microlithiasis (TML) is a premalignant condition. This study's objective was to investigate TML histology prevalence in testicular cancer patients in two European populations. METHODS: We analysed archived histopathology orchiectomy specimens from 152 patients diagnosed with testicular cancer at Fredericia Hospital in Denmark from 2004 to 2014, and 106 patients diagnosed at St Thomas' Hospital in London from 2011 to 2015. RESULTS: The Danish patients' median age was 37 years (range: 16-74 years) and the English patients' 36 years (range: 18-78 years). In the Danish patients, 29 (19.1%) had TML, and in the English patients, 43 (40.6%) had TML (p < 0.001). Haematoxylin bodies were slightly more common in the English patients. Laminated calcification was more often seen in seminomas than in non-seminomas. CONCLUSIONS: The English testicular cancer patients had a statistically significantly higher TML prevalence than the Danish patients. This observation questions the hypothesised biological association between TML and testicular cancer. FUNDING: The Region of Southern Denmark supported this study. TRIAL REGISTRATION: not relevant.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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 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

Citations9
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicTesticular diseases and treatmentsFrench-language works237,207