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Record W2584125249 · doi:10.15173/m.v1i27.1164

Glioblastoma Tumours: Complex Challenges and Deadly Outcomes

2016· article· en· W2584125249 on OpenAlexvenueno aff
Alexandra Kilian

Bibliographic record

VenueThe Meducator · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsGlioblastomaMedicineCancer research

Abstract

fetched live from OpenAlex

Glioblastoma (GBM) tumours are the most common primary brain tumours among adults, with many treatment challenges. In addition to being highly malignant and fatal tumours, GBMs are also heterogeneous in tissue and genetic composition, difficult to target, frequently recurring and often treatment-resistant. As a result of these challenges, GBM treatment has been essentially unchanged for decades, with minute improvements in patient prognosis, despite active research efforts. Currently, patients have a mean survival time of less than fifteen months. This article aims to explore the current questions in GBM research, including the role and limitations of surgery and chemotherapy treatments, the relationship between age and prognosis, and the controversy surrounding the optimal extent of resection. Additionally, this article outlines the impact of notable research developments in the field, including the role of nanotechnology in the first successful chemo-radiotherapy treatment on otherwise treatment-resistant GBM cells.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

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

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 head0.046
GPT teacher head0.301
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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