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Record W4385650136 · doi:10.3390/curroncol30080541

Phosphaturic Mesenchymal Tumors with or without Phosphate Metabolism Derangements

2023· review· en· W4385650136 on OpenAlexvenueno aff
Maria Giulia Pirini, Ludovica Lotrecchiano, Lorenzo Di Prinzio, Guido Zavatta

Bibliographic record

VenueCurrent Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteomalaciaMesenchymal stem cellNarrative reviewDiseasePathologyBioinformaticsIntensive care medicineInternal medicineVitamin D and neurology

Abstract

fetched live from OpenAlex

Phosphaturic mesenchymal tumors (PMT) are rare neoplasms, which can give rise to a multifaceted syndrome, otherwise called tumor-induced osteomalacia (TIO). Localizing these tumors is crucial to obtain a cure for the phosphate metabolism derangement, which is often the main cause leading the patient to seek medical help, because of invalidating physical and neuromuscular symptoms. A proportion of these tumors is completely silent and may grow unnoticed, unless they become large enough to produce pain or discomfort. FGF-23 can be produced by several benign or malignant PMTs. The phosphate metabolism, radiology and histology of these rare tumors must be collectively assessed by a multidisciplinary team aimed at curing the disease locally and improving patients' quality of life. This narrative review, authored by multiple specialists of a tertiary care hospital center, will describe endocrine, radiological and histological features of these tumors, as well as present surgical and interventional strategies to manage PMTs.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.254
GPT teacher head0.491
Teacher spread0.237 · 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 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

Citations18
Published2023
Admission routes1
Has abstractyes

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