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Record W2790570326 · doi:10.1530/erc-18-0015

65 YEARS OF THE DOUBLE HELIX: Treatment of pituitary tumors with temozolomide: an update

2018· review· en· W2790570326 on OpenAlexaff
Luis V. Syro, Fabio Rotondo, León Darío Ortiz, Kálmán Kovács

Bibliographic record

VenueEndocrine Related Cancer · 2018
Typereview
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsTemozolomideMedicinePituitary tumorsAnaplastic astrocytomaOncologyInternal medicineGlioblastomaAdjuvantAdjuvant therapyPituitary adenomaAstrocytomaMelanomaCancer researchChemotherapyAdenoma

Abstract

fetched live from OpenAlex

Temozolomide is an alkylating chemotherapeutic agent used in malignant neuroendocrine neoplasia, melanoma, brain metastases and an essential component of adjuvant therapy in the treatment of glioblastoma multiforme and anaplastic astrocytoma. Since 2006, it has been used for the treatment of pituitary carcinomas and aggressive pituitary adenomas. Here, we discuss the current indications and results of temozolomide therapy in pituitary tumors, as well as frequently asked questions regarding temozolomide treatment, duration of therapy, dosage, tumor recurrence and resistance.

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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.032
GPT teacher head0.338
Teacher spread0.307 · 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

Citations22
Published2018
Admission routes1
Has abstractyes

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