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Record W2340054771 · doi:10.1080/17446651.2016.1179110

Biomarkers of pituitary carcinomas

2016· article· en· W2340054771 on OpenAlexaff
Aydın Sav, Fabio Rotondo, Luis V. Syro, Antonio Di Ieva, Michael D. Cusimano, Kálmán Kovács

Bibliographic record

VenueExpert Review of Endocrinology & Metabolism · 2016
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsCarcinogenesisCancer researchPituitary adenomaMalignant transformationMedicineBiomarkerPTENTelomeraseCancerBiologyBioinformaticsAdenomaPathologyInternal medicineSignal transductionGeneGenetics

Abstract

fetched live from OpenAlex

INTRODUCTION: Pituitary carcinoma is a rare tumor originating from adenohypophyseal cells. Currently, diverse pathogenetic mechanisms, i.e. de novo versus malignant transformation from pituitary adenoma, remain obscure and require further investigation. During the last two decades, scientific research added new horizons not only in regards to general tumor concepts but also in next generation biomarker armamentarium that sheds light on alternate pathways in carcinogenesis. Areas covered: In this review, the impact of apoptotic and proliferative markers, angiogenesis, telomerase activity, H-ras, HIF-1, HER-2/neu, Rb gene, and microRNAs in pathogenetic mechanisms of pituitary carcinomas were revised. Expert commentary: It is becoming increasingly important for the need of standardization of new biomarkers but also for better comprehension of the diverse pathways in tumorigenesis. This can only be accomplished by tapping into the continuously expanding spectrum of new biomarkers.

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: none
Teacher disagreement score0.630
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.018
GPT teacher head0.310
Teacher spread0.292 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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