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Record W2041516550 · doi:10.1088/0031-9155/52/21/014

Myelin structure is a key difference in the x-ray scattering signature between meningioma, schwannoma and glioblastoma multiforme

2007· article· en· W2041516550 on OpenAlexafffund
Greg Falzon, Sarah Pearson, R. D. Murison, C.J. Hall, Karen K. W. Siu, Adam Round, Elisabeth Schültke, Andrew H. Kaye, Robert A. Lewis

Bibliographic record

VenuePhysics in Medicine and Biology · 2007
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Applications
Canadian institutionsUniversity of Saskatchewan
FundersRoyal University Hospital FoundationUniversity of Saskatchewan
KeywordsSchwannomaMeningiomaGlioblastomaMyelin sheathMyelinScatteringPathologyGliomaMedicineRadiologyPhysicsOpticsInternal medicineCancer researchCentral nervous system

Abstract

fetched live from OpenAlex

Small angle x-ray scattering (SAXS) patterns of benign and malignant brain tumour tissue were examined. Independent component analysis was used to find a feature set representing the images collected. A set of coefficients was then used to describe each image, which allowed the use of the statistical technique of flexible discriminant analysis to discover a hidden order in the data set. The key difference was found to be in the intensity and spectral content of the second and fourth order myelin scattering peaks. This has clearly demonstrated that significant differences in the structure of myelin exist in the highly malignant glioblastoma multiforme as opposed to the benign: meningioma and schwannoma.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.267

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 head0.078
GPT teacher head0.340
Teacher spread0.262 · 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

Citations16
Published2007
Admission routes2
Has abstractyes

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