MétaCan
Menu
Back to cohort
Record W2074000588 · doi:10.1097/rct.0b013e3181f56fda

Is Brain SPECT Useful in Degenerative Dementia Diagnosis?

2010· review· en· W2074000588 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

VenueJournal of Computer Assisted Tomography · 2010
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineDementiaSingle-photon emission computed tomographyCerebral blood flowDegenerative diseaseEmission computed tomographyDifferential diagnosisPositron emission tomographyMedical diagnosisDiseaseAlzheimer's diseaseNeuroscienceRadiologyPathologyCardiology

Abstract

fetched live from OpenAlex

Cerebral blood flow assessment performed by single-photon emission computed tomography (SPECT) of the brain is used to detect early neuronal dysfunction associated with degenerative dementia. Patterns of perfusion abnormalities are different across dementia syndromes. These differences could be used for differential diagnoses and early detection of amnesic mild cognitive impairment in patients with a high risk of conversion to Alzheimer disease. This paper aimed to summarize the expected benefits of single-photon emission computed tomography of the brain in the exploration of degenerative dementias.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.372
Teacher spread0.322 · 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