MétaCan
Menu
Back to cohort
Record W2037227294 · doi:10.2174/1874440001408010005

Enhanced Power Within the Default Mode Network in Normal Subjects with Elevated Scores on an Egocentric Scale

2014· article· en· W2037227294 on OpenAlexaff
Mark Collins, Michael A. Persinger

Bibliographic record

VenueThe Open Neuroimaging Journal · 2014
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEgocentrismDefault mode networkPsychologyLateralization of brain functionPower (physics)Scale (ratio)Mode (computer interface)CognitionDevelopmental psychologyCognitive psychologyNeuroscienceGeographyCartography

Abstract

fetched live from OpenAlex

Integrated global power from the primary structures that composed the Default Mode Network (DMN) and from a random collection of other structures were measured by sLORETA (standardized low-resolution electromagnetic tomography) for young university volunteers who had completed an inventory that contained a subscale by which egocentricity has been inferred. Subjects who exhibited higher scores for egocentricity displayed significantly more power within the DMN structures relative to comparison areas. This was not observed for individuals whose egocentricity scores were lowest where the power differences between the DMN and comparison structures were not significant statistically. DMN power was greater in the right hemisphere than the left for men but greater in the left hemisphere than the right for women. The results are consistent with our operating metaphor that elevation of power or activity within the DMN is associated with greater affiliation with the self and its cognitive contents.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.383
Teacher spread0.343 · 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 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueThe Open Neuroimaging JournalSame topicMental Health Research TopicsFrench-language works237,207