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Record W2051739370 · doi:10.2174/1874440001307010001

Long-Wave Infrared Functional Brain Imaging in Human: A Pilot Study

2013· article· en· W2051739370 on OpenAlexaff
Christian C. Joyal, Mylène Henry

Bibliographic record

VenueThe Open Neuroimaging Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsUniversité du Québec à Trois-RivièresInstitut national de psychiatrie légale Philippe-PinelUniversité du Québec à Montréal
Fundersnot available
KeywordsStroop effectNeuropsychologyPsychologyNeuroscienceFrontal cortexNeuroimagingAudiologyCognitive psychologyCognitionMedicine

Abstract

fetched live from OpenAlex

Although some authors suggest to use Long-Wave Infrared (LWIR) sensors to evaluate brain functioning, the link between emissions of LWIR and mental effort is not established. The goal of this pilot study was to determine whether frontal LWIR emissions vary during execution of neuropsychological tasks known to differentially activate the pre-frontal cortex (simple color presentations, induction of the Stroop effect, and a gambling task with real money). Surprisingly, LWIR emissions as measured with bilateral frontal sensors in 47 participants significantly differed between tasks, in the supposed direction (Color<Stroop

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.316
Teacher spread0.253 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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