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Record W2581833031 · doi:10.1177/1754073916667237

Hierarchical Brain Systems Support Multiple Representations of Valence and Mixed Affect

2017· article· en· W2581833031 on OpenAlex

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

VenueEmotion Review · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsValence (chemistry)PsychologyNegativity effectCognitive psychologyAffect (linguistics)Negativity biasSocial psychologyCommunication

Abstract

fetched live from OpenAlex

We review the psychological literature on the organization of valence, discussing theoretical perspectives that favor a single dimension of valence, multiple valence dimensions, and positivity and negativity as dynamic and flexible properties of mental experience that are contingent upon context. Turning to the neuroscience literature that spans three levels of analysis, we discuss how positivity and negativity can be represented in the brain. We show that the evidence points toward both separable and overlapping brain systems that support affective processes depending on the level of resolution studied. We move from large-scale brain networks that underlie generalized processing, to functionally specific subcircuits, finally to intraregional neuronal distributions, where the organization and interaction across levels allow for multiple types of valence and mixed evaluations.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.060
GPT teacher head0.335
Teacher spread0.276 · 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