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Record W4405392299 · doi:10.70121/001c.127452

Understanding PTSD: Impacts on Memory, Brain Structure, and the Formation of False Memories

2024· article· en· W4405392299 on OpenAlexfundno aff
Kushal Madhabhaktula

Bibliographic record

VenueScholarly review . · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
FundersBrock University
KeywordsHypervigilanceFalse memoryPsychologyTraumatic memoriesPosttraumatic stressMemory problemsAffect (linguistics)Autobiographical memoryPsychiatryClinical psychologyCognitive psychologyMedicineAnxietyCognitionDiseaseDementia

Abstract

fetched live from OpenAlex

Post Traumatic Stress Disorder (PTSD) is a mental health condition triggered by exposure to traumatic events. These traumatic events could range from natural disaster traumas to abuse and war traumas. PTSD is usually found in individuals who have served their nation but can be found in anyone who has been exposed to trauma. It is important to understand the causes of PTSD as many individuals suffer improper sleeping patterns and hypervigilance and try to detach themselves from the world. The purpose of this paper is to describe what PTSD is, how it can affect memory loss, and how it can form false memories. PTSD can be harmful if untreated, especially if the patient is isolated. Neurologists have identified that PTSD can cause memory loss and can create false memories; however, treatments for PTSD are developing rapidly such as EMDR which can reduce the probability of developing memory loss and false memories in the future.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.114
GPT teacher head0.332
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreReview

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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