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Brain Metastases: State of the Art and Innovative Targeted Therapies

2015· article· en· W2303714973 on OpenAlexvenueno aff
Maria Caffo, Lucia Merlo, Valeria Barresi, Ema Tot, Gerardo Caruso

Bibliographic record

VenueJournal of Analytical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsExtravasationMedicineBrain metastasisMetastasisRadiation therapyCancerBrain cancerBlood–brain barrierTargeted therapyDiseaseCancer researchPathologyInternal medicineCentral nervous system

Abstract

fetched live from OpenAlex

Brain metastasis represents the most common intracranial tumor. The metastatic process involves the migration of a cancer cell from the bulk tumor into the surrounding tissue, extravasation from the blood vessels into the tissues, and formation of a secondary tumor. Patients affected by brain metastases are in need of a multidisciplinary approach that generally includes surgical treatment and radiation therapy. Conventional chemotherapies have generally produced disappointing results, possibly due to their limited ability to penetrate the blood-brain barrier. With new data regarding the biology of brain metastases, novel targeted therapies can be considered interesting and promising therapeutic options. Targeted therapies showed improved survival in patients with metastatic disease. The advent of new technologies such as graphene nanoparticles has led to the discovery of novel pathways that allow a better delivery of the therapeutic compounds to the brain.

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)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.352
Teacher spread0.309 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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