The Cambridge Handbook of Human Affective Neuroscience
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.
Bibliographic record
Abstract
Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it