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Record W2485972902 · doi:10.1007/7657_2012_39

Assessing Mechanisms of Glioblastoma Invasion

2012· book-chapter· en· W2485972902 on OpenAlexaff
Stephen M. Robbins, Donna L. Senger

Bibliographic record

VenueNeuromethods · 2012
Typebook-chapter
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInfiltration (HVAC)BiologyGlioblastomaBasement membraneBrain cancerPopulationNeuroscienceIn vivoCellParenchymaGliomaCancer cellCancer researchCancerPathologyMedicineCell biology

Abstract

fetched live from OpenAlex

Glioblastomas are one of the deadliest and most invasive cancers in humans. This heterogenous population of tumours interact with the surrounding brain parenchyma, disrupting physical barriers such as basement membranes, extracellular matrices and cell–cell contact while activating cellular processes that enable infiltration of cells long distances away from the original tumour mass. The protocols describe in this chapter aim to establish experimental models, both in vitro and in vivo, as tools for discovery and evaluation of the underlying molecular mechanisms of cellular invasion by providing experimental methodology that recapitulate, as close as possible, the tumour microenvironment in humans. Although established for the assessment of glioma migration and invasion, these methods provide experimental platforms that can be easily adapted for different types of cancers and for the screening of candidate cancer therapeutics.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.355
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0030.001

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 head0.059
GPT teacher head0.311
Teacher spread0.253 · 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.

Study designBench or experimental
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

Citations2
Published2012
Admission routes1
Has abstractyes

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