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Record W4405574003 · doi:10.1080/13554794.2024.2442010

Inner dialogue dysfunction and the abusive comments of the dominant hemisphere

2024· article· en· W4405574003 on OpenAlexaff
Luis Fornazzari, Mila Valcic, Matthew Juhasz, Corinne E. Fischer

Bibliographic record

VenueNeurocase · 2024
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsPsychologyRight hemisphereCognitive psychology

Abstract

fetched live from OpenAlex

Inner dialogue and inner speech are normal systems of cerebral intrapersonal communication, crucial to self-awareness. Lesions affecting the cerebral network involved in these systems have been associated with the occurrence of Auditory Verbal Hallucinations (AVHs). These are regarde as a continuum phenomenon experienced by healthy, individuals, as well as those with psychiatric disorders. In this paper, two patients with left hemispheric lesions of different pathologies, vascular and tumor, respectively, who during their recovery of motor and sensory functions presented severe deregulation in their inner dialogue. In both cases, the damaged left dominant hemisphere adopted arrogant, demeaning, and abusive inner speech, while the right non-dominant side, which commands the rehabilitation of the lost functions, was subdued and quiet. This abusive unilateral inner dialogue was present until adequate recovery of independent functions was achieved for both patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.308
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2024
Admission routes1
Has abstractyes

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