Cerebral Activity and Source Profiles Accompanying the Process of Non-Locality
Bibliographic record
Abstract
The independently rated congruence of subjects’ drawings and descriptions with the content of affective pictures hidden ~50 m away were correlated with cerebral quantitative electroencephalography (QEEG) and LORTEA (Low Resolution Electromagnetic Tomography) over three weekly trials. A shift over time from left prefrontal gamma activity to right caudal hemispheric delta activity was associated with increased accuracy. Increased accuracies for the details for the non-local stimuli during sessions were associated with greater congruence within the 25-30 Hz and theta (4-7 Hz) range between the parahippocampal regions. Increased theta power also occurred in the left anterior cingulate, fusiform gyrus and midtemporal regions. We suggest that experiences of non-locality involve confluence within the right parahippocampal region and are translated for their personal and linguistic equivalents within specific left hemispheric structures. NeuroQuantology | September 2013 | Volume 11 | Issue 3 | Page 378-390
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".