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Aversive motivation systems: fear, frustration and aggression

2000· book-chapter· en· W192179668 on OpenAlexaff
Roderick Wong

Bibliographic record

VenueCambridge University Press eBooks · 2000
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFrustrationAggressionPsychologySocial psychology

Abstract

fetched live from OpenAlex

When animals are exposed to aversive stimuli, particularly those of pain, they are likely to respond by either withdrawing from or attacking the source of the stimuli. ‘Pain is an anatomically developed sensory system genetically differentiated for survival and the defence of the body. Responses to painful stimuli either involve the skeletal musculature or are internal but they are experimentally quantified as escape and avoidance’ (Le Magnen, 1998, p. 4). Both types of responses to this source serve adaptive functions. In many species, specific escape mechanisms have evolved for dealing with physical danger. One of the simplest is the withdrawal reflex that removes the organism from damaging stimuli. When specific taste receptors are in contact with bitter substances, they result in a spitting reflex that protects the organism from ingesting possibly toxic substances that are generally associated with the bitter taste. In Chapter 5 the mechanisms by which rats learn to avoid smells and tastes that have previously been followed by illness were examined. Animals will also react to aversive stimuli with attack behaviour, particularly when escape is difficult. Such a reaction is particularly evident in feral animals. TWO-FACTOR THEORY OF AVOIDANCE BEHAVIOUR The standard situation or apparatus used to study responses to aversive stimuli is one in which a rat is placed in a shuttle box – a long narrow box divided in half by a partition. The floor of the box is a grid of steel rods that can can deliver a painful shock when activated by electricity. The rules of the experiment are as follows. The rat has a few seconds to cross the barrier over to the other side of the box.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.039
GPT teacher head0.223
Teacher spread0.183 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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