Visual Perception Part 2: Fundamentals of Awareness, Multi-Sensory Integration and Higher-Order Perception
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
Susana Martinez-Conde, PhD, Stephen L. Macknik, PhD, Luis M. Martinez, PhD, Jose-Manuel Alonso, PhD, and Peter U. Tse, PhD, Editors. Elsevier, Amsterdam, 2006. ISBN 978-0-444-51927-6, $250.00. Scope: This is the second volume of a series entitled Visual Perception. It is based on the symposia presented at the European Conference on Visual Perception (ECVP) 2005, held in Spain. The book is divided into four sections, each consisting of a collection of selected papers covering a topic in vision science. The first section, entitled The Role of Context in Recognition, deals with recognition of higher-level visual objects and explores how top-down influences and context-based information affect object recognition. The second section, entitled From Perceptive Fields to Gestalt: a Tribute to Lothar Spillmann, includes papers presented at the special symposium in honor of one of the founders of ECVP, as well as the plenary lecture of Dr. Spillmann. The third section, entitled The Neural Basis for Visual Awareness and Attention, brings together five articles that cover aspects of visual awareness, including blindsight, binocular rivalry, attention, and visual masking. The fourth section, entitled Cross-Modal Interactions in Visual Perception, contains articles that investigate issues ranging from exploration of synesthesia to investigations on how information from auditory and visual modalities is integrated into a unique percept. Strengths: The quality of articles is consistently high. The authors are well-respected researchers. Each article serves as a mini-review that summarizes work done in recent years. Different viewpoints and methodologies are represented. Dr. Spillmann's plenary lecture inspiringly describes the creative and collaborative atmosphere in his Freiburg laboratory that brought together many generations of distinguished scientists. Weaknesses: The different sections of the book do not particularly mesh together and read more like independent pieces. Hence the somewhat cumbersome title, which falls short of communicating the contents of the book. Recommended Audience: All students of visual sciences, including sensory and cognitive neuroscientists will find this book useful. Critical Appraisal: This book includes state-of-the-art mini-reviews of a range of visual and multisensory topics, featuring summaries of cutting-edge research from across the field. Ipek Oruç, PhD Jason J. S. Barton, MD, PhD Human Vision and Eye Movement Laboratory University of British Columbia Vancouver, British Columbia
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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