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Record W4412672271 · doi:10.1017/9781009450966.014

Breaking New Ground: Novel Approaches to Understanding Catatonia and the Brain–Mind Relationship

2025· book-chapter· en· W4412672271 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2025
Typebook-chapter
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCatatoniaCognitive sciencePsychologyNeuroscienceSchizophrenia (object-oriented programming)Psychiatry

Abstract

fetched live from OpenAlex

Over the past three decades, catatonia research has experienced a remarkable renaissance, driven by the application of diverse methodologies and conceptual frameworks. This renewed interest has significantly reshaped our understanding of catatonia, a complex syndrome with multifactorial origins spanning epidemiology, historical context, phenomenology, genetics, immunology, and neurobiology. These advancements have offered a more comprehensive and nuanced perspective, culminating in the recognition of catatonia as a distinct diagnosis in the ICD-11 – a landmark development that underscores its clinical and scientific relevance. Despite these strides, several unresolved issues remain that require future research. Bridging these gaps is crucial not only to enhance our understanding of catatonia but also to identify the most effective treatments and uncover the mechanisms underlying their efficacy. Such advancements hold the promise of developing improved diagnostic markers and tailored therapeutic strategies, offering significant benefits to patients affected by this challenging condition. In this chapter, we explore the profound implications of catatonia research, spanning its impact on clinical psychiatry and neuroscience, as well as its broader contributions to our understanding of the intricate relationship between the brain and mind.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.163
GPT teacher head0.246
Teacher spread0.083 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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