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Record W2657857444 · doi:10.1109/isbi.2017.7950575

Brain geometry persistent homology marker for Parkinson's disease

2017· article· en· W2657857444 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTopological and Geometric Data Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPersistent homologyTopological data analysisPoint cloudPersistence (discontinuity)Homology (biology)TimelineTopology (electrical circuits)GeometryNeurodegenerationComputer scienceMathematicsDiseaseMedicineArtificial intelligenceBiologyPathologyCombinatoricsGeneticsAlgorithmStatistics

Abstract

fetched live from OpenAlex

The geometry of the human brain changes due to age and neurodegeneration. The brain geometry is expected to undergo a similar change in shape with a normal aging, however such change may differ in patients suffering from neurodegenerative disorders. In the novel framework proposed in this work, we model the brain geometry as a 3D point cloud and study the algebraic topology features of this point cloud. Specifically, we compute the persistence timelines of a simplicial complex in a multiscale simplicial homology of the underlying topology space. Further, persistence landscape summary features are obtained from the timelines and studied for their difference between the two groups. The statistical significance obtained in a permutation testing experiments highlights the ability of the persistence landscape features to differentiate between the PD and healthy control brain geometry.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0020.001
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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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