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Record W2013430002 · doi:10.2466/pms.2003.96.3.965

Intermittent Burst-Firing Weak (1 microTesla) Magnetic Fields Reduce Psychometric Depression in Patients Who Sustained Closed Head Injuries: A Replication and Electroencephalographic Validation

2003· article· en· W2013430002 on OpenAlex
Laura Baker-Price, Michael A. Persinger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerceptual and Motor Skills · 2003
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsLaurentian University
Fundersnot available
KeywordsDepression (economics)ElectroencephalographyTemporal lobeStimulationPsychologyPrefrontal cortexMagnetic resonance imagingAudiologyMedicineAnesthesiaEpilepsyNeuroscienceRadiologyCognition

Abstract

fetched live from OpenAlex

14 patients who reported chronic depression more than one year after closed head injuries were exposed to weak (1 microTesla), burst-firing magnetic fields either across the temporal lobes or over the left frontal lobe. The treatment was for 30 min. once per week for 6 wk. The reduction in depression scores after 5 wk. of treatments and after 6 wk. of no treatment (follow-up) accommodated 54% of the variance for both groups. The changes in depression scores did not differ significantly between the two groups (temporal vs frontal). Following treatment, the frequency of complex partial epileptic-like experiences decreased significantly only for the 7 who received the bilateral stimulation over the temporal lobes. Quantitative bipolar electroencephalographic measurements over the occipital, prefrontal, and temporal regions showed increased power within the 16-Hz to 18-Hz range 6 wk. after termination of treatment for those 7 patients who received the burst-firing magnetic fields bilaterally over the temporal lobes but not over the left prefrontal region.

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.

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)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.263
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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