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Neurochemical brain imaging studies in bipolar disorder

2003· article· en· W2151469740 on OpenAlexaff
Lakshmi N. Yatham, Gin S. Malhi

Bibliographic record

VenueActa Neuropsychiatrica · 2003
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeurochemicalNeuroscienceBipolar disorderSerotonergicMedicinePsychologyPsychiatryInternal medicineCognitionSerotonin

Abstract

fetched live from OpenAlex

OBJECTIVE: We reviewed the neurochemical brain imaging literature in bipolar disorder to synthesize the findings and provide directions for future research. METHODS: Relevant articles were retrieved by computerized Medline Ovid search (up to and including 2002) and complemented by bibliographic manual searches of reviews known to the authors. RESULTS: PET and SPECT studies in bipolar disorder have identified changes in various aspects of dopaminergic and serotonergic neurotransmission. Ligands for other neurotransmitters are actively being pursued. Spectroscopy studies have utilized a number of MRS-sensitive nuclei to chemically 'biopsy' the brain of patients with bipolar disorder. Few consistent findings are emerging, however, the majority of nuclei that can be measured are not directly related to the pathophysiology of the disorder. CONCLUSIONS: Brain imaging has the potential to unravel the neurochemical underpinnings of bipolar disorder, however, there is a continuing need for clinical, technical and methodological sophistication.

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 score0.599
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.303
Teacher spread0.284 · 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

Citations10
Published2003
Admission routes1
Has abstractyes

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