Short-term consolidation of individual identities leads to Lag-1 sparing.
Bibliographic record
Abstract
A rapid serial visual presentation (RSVP) technique was used to investigate the role of the nature of processing carried out on targets in the Lag-1 sparing phenomenon. Lag-1 sparing refers to a higher accuracy in the task associated with the 2nd target when the 2 targets are immediately successive in the RSVP stream relative to when there are 1 or 2 intervening items between the targets. In 5 experiments, 0, 1, or 2 digits were embedded with equal probability in RSVP streams of letter distractors. In 4 of the experiments, subjects identified the digits in some blocks of trials, and they counted the number of presented digits in other blocks. In a 5th experiment, the counting task was replaced with a digit-sum task. The most interesting results were those from trials with 2 digits. Lag-1 sparing was always evident when the task involved the explicit identification of the digits. In addition, Lag-1 sparing was evident when subjects were required to sum 2 digits or to count digits of a prespecified parity subclass (e.g., count only even digits). In striking contrast, Lag-1 sparing was absent when subjects were required to count the digits independent of their parity subclass. These results suggest that the occurrence of Lag-1 sparing depends on the type of mental representation that must be generated on the basis of target information.
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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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".