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
We have previously shown that when observers are presented with complex natural scenes that contain a number of objects and people, observers look mostly at the eyes of the people. Why is this? It cannot be because eyes are merely the most salient area in a scene, as relative to other objects they are fairly inconspicuous. We hypothesized that people look at the eyes because they consider the eyes to be a rich source of information. To test this idea, we tested two groups of participants. One set of participants, called the Told Group, was informed that there would be a recognition test after they were shown the natural scenes. The second set, the Not Told Group, was not informed that there would be a subsequent recognition test. Our data showed that during the initial and test viewings, the Told Group fixated the eyes more frequently than the Not Told group, supporting the idea that the eyes are considered an informative region in social scenes. Converging evidence for this interpretation is that the Not Told Group fixated the eyes more frequently in the test session than in the study session.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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