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Record W2124340921 · doi:10.2217/17520363.2.3.229

Spectroscopy of Human Plasma for Diagnosis of Idiopathic Parkinson S Disease

2008· article· en· W2124340921 on OpenAlexaff
Hyman M. Schipper, Chun Shing Kwok, Scott M. Rosendahl, Dirk Bandilla, Olivier Maës, Calvin Melmed, Daniel Rabinovitch, David H. Burns

Bibliographic record

VenueBiomarkers in Medicine · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineHuman plasmaChromatography

Abstract

fetched live from OpenAlex

BACKGROUND: No established chemical biomarkers of idiopathic Parkinson's disease (PD) currently exist. Augmented oxidative stress (OS) has been implicated in both neural and peripheral PD tissues. METHODS: In this study, Raman scattering and near-infrared spectroscopy were used to detect and quantify oxidative substrate modifications in blood plasma samples from PD and normal elderly control (NEC) subjects. RESULTS: Hypothesis-driven preselection of OS-sensitive bandwidths distinguished PD from NEC subjects with approximately 75% sensitivity and specificity using both complementary spectroscopic techniques. CONCLUSION: Biospectroscopy of plasma may provide a rapid, minimally invasive and inexpensive chemical biomarker of idiopathic PD.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.439

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 studies0.0000.001
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 head0.027
GPT teacher head0.347
Teacher spread0.320 · 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 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

Citations31
Published2008
Admission routes1
Has abstractyes

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