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Record W3081056070 · doi:10.1097/cco.0000000000000679

Mechanisms of invasion in glioblastoma

2020· review· en· W3081056070 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Opinion in Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchAgence Nationale de la Recherche
KeywordsGlioblastomaTumor microenvironmentBiologyNeuroscienceCancer researchMedicineTumor cells

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review provides an overview of recent updates in understanding the mechanisms by which glioblastoma cells interact with their cellular and molecular partners within the microenvironment. RECENT FINDINGS: We have now a better knowledge of the cell populations involved in Glioblastoma (GBM) invasion. Recent works discovered the role of new molecular players in GBM invasion, and, most importantly, better models are emerging which better recapitulate GBM invasion. SUMMARY: Invasive properties of glioblastoma make complete surgical resection impossible and highly invasive cells are responsible for tumor recurrence. In this review, we focus on recent updates describing how invasive cells progress in the surrounding tissue along brain structures. We also provide an overview of the current knowledge on key cells and molecular players within the microenvironment that contribute to the invasive process. VIDEO ABSTRACT.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.439
Teacher spread0.302 · 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