Bibliographic record
Abstract
Seeing SeeingThe past decades have seen great progress in our understanding of human visual perception.Important advances have occurred both in the techniques used and the conceptual frameworks developed.The result has been a great increase in our understanding of how we see, and the way that consciousness enters into it.Amidst all this, however, confusion has arisen on several fronts about particular issues, even to some extent about the bigger picture that is emerging.Part of this is due to inconsistencies in several of the technical terms used, which have retained some of the vagueness and ambiguity found in their original use in everyday language.Another source of confusion is the fact that many of the discoveries were converged on by researchers from different traditions, bringing with them different terminologies and styles of analysis.Finally, a certain amount of confusion is inevitable simply because progress has been so rapid, and our understanding still so incomplete.There are conceptual gaps and inconsistencies yet to be addressed, hindering our ability to obtain a clear picture of the situation.But although some of this confusion cannot be dispelled at the moment, much of it can.The goal here is to present a reasonably consistent (although necessarily incomplete) account of several key issues concerning conscious and nonconscious processes in vision, and to discuss some of the questions that still need to be answered. Rapid VisionWhen discussing visual perception, a natural place to begin is rapid vision, which comprises those processes occurring within the first few hundred milliseconds or so of stimulus onset (see e.g., Rensink & Enns, 1995, 1998).This aspect of vision is dominated by feedforward information flow: within 150 milliseconds this "first wave" can reach all areas of cortex (e.g., Lamme & Roelfsma, 2000).Rapid vision itself can be decomposed further based on distance from the initial input at the retina.Processes at the lowest levels involve retinotopic representations; at slightly higher levels, they become increasingly spatiotopic, involving relative rather than absolute spatial locations.All these processes are highly parallel, with operations carried out concurrently at many-and perhaps most-locations in the visual field.Processes that are both rapid and low-level constitute what is known as early vision.Historically, early processes were identified as "preattentive", i.e., acting before attention had a chance to operate.In this view, simple features were formed at this level (such as bars or colored patches) and then combined by visual attention into more complete objects (e.g., Treisman & Gormican, 1988).However, it has been found that relatively complex "protoobjects" of limited extent (a few degrees of visual angle) can be formed at this level, involving
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.414 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".