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Record W4313635712 · doi:10.5937/scriptamed53-38283

Renal tumours of childhood: A review

2022· review· en· W4313635712 on OpenAlexaboutno aff
Gordan Vujanić, S Duricić

Bibliographic record

VenueScripta Medica · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWilms tumourClear-cell sarcomaRenal cell carcinomaChemotherapyPediatric oncologyWilms' tumorOncologySarcomaInternal medicinePathologyCancer

Abstract

fetched live from OpenAlex

Renal tumours of childhood are rare, although they are one of the most common solid tumours in children. They include numerous entities, which have different clinical, histological, molecular biological and prognostic features, so their precise diagnosis and staging are critical for appropriate treatment. The most common is Wilms' tumour (WT) with ~80-85 % of all cases, whereas other entities including mesoblastic nephroma, clear cell sarcoma, rhabdoid tumour, renal cell carcinoma, metanephric tumours and others are very rare (2-4 % each) which explains why they represent a big diagnostic challenge for diagnostic pathologists. They are subclassified into three risk groups - low, intermediate and high - which have different treatments and prognosis. There are two big study groups which have different approaches but remarkable similar outcomes. The International Society of Paediatric Oncology approach (followed in most of the world) is based on preoperative chemotherapy, followed by surgery and further therapy, whereas the Children's Oncology Group approach (followed mainly in the United States and Canada) is based on primary surgery, followed by postoperative treatment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.742
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.297
Teacher spread0.275 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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