What can 9 million trials tell us about memorability in a hybrid search task?
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
Hybrid visual search tasks involve searching for multiple targets held in memory, but some targets are more memorable than others. Furthermore, some items are readily identified as being in the memory set, while others are readily identified as not being in the memory set; these may be considered to vary in their “hittability” and “rejectability”, respectively. In principle, both factors should impact error rates and reaction times in hybrid search. Using a set of 9 million trials from an online hybrid search game, we analyze participants’ errors and show that hittability and rejectability are largely separable. It is possible for items to be rejectable without being particularly hittable, and to be hittable without being particularly rejectable. Both factors are consistent across participants and stable across age, training, and performance. Rejectability strongly predicted reaction times in the search for new items, while hittability was more weakly associated with reaction times.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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