Three Semantic Serial Position Functions at the Same Time
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
Serial position functions are so ubiquitous that researchers frequently use buffer items to control for primacy and recency effects regardless of the memory task. However, most theories offer different explanations for different types of tests. In contrast, the relative distinctiveness principle offers one explanation for all tasks: items with fewer close neighbors will generally be more distinct and therefore better remembered than items with more close neighbors. An experiment assessed two predictions of this account. (1) When undergraduates place seven US states in three different orders (by area, year of statehood, and population), serial position functions and error gradients will be observed that resemble those observed in episodic tasks. (2) States that are accurately placed in order because they are an early or late item on one dimension will be placed in order far less accurately when they become mid-list items on a different dimension. The results confirm both predictions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.016 |
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