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Record W2462388438 · doi:10.1051/medsci/2003191118

La mémoire aux prises avec les émotions et le stress : un impact nécessairement dommageable?

2003· review· fr· W2462388438 on OpenAlexaff
Françoise S. Maheu, Sonia J. Lupienn

Bibliographic record

Venuemédecine/sciences · 2003
Typereview
Languagefr
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsDouglas Mental Health University InstituteDouglas College
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

While intense negative events are vividly recalled, information learned during stressful situations is poorly remembered. These differential effects of emotions and stress on memory have been attributed to the physiological manifestations generated during those affective states. Intense emotional and stressful events trigger the secretion of catecholamines and of glucocorticoids, in particular. These hormones would be modulatory agents of memory functions. In the first part of this paper, we review the specific effects emotions and stress have on memory. We then summarize the psychological and biological determinants responsible for these effects. Finally, we discuss different methodological issues that could explain the discrepancy found between the impact of emotions and stress on memory. Defining more precisely the effects emotion and stress have on memory will lead to a better comprehension of the cognitive problems that characterize patients dealing with emotional turmoil, such as patients suffering from depression or post-traumatic stress disorder.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.104
GPT teacher head0.384
Teacher spread0.280 · 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

Citations18
Published2003
Admission routes1
Has abstractyes

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