When lust is lost: Orthographic similarity effects in the encoding and reconstruction of rapidly presented word lists.
Bibliographic record
Abstract
A reconstructive account of memory is presented to explain the finding that report of a word (C2) appearing in a rapidly presented list is reduced when it is orthographically similar to an earlier word (C1) in the list. By this account, the effect arises when the list is reconstructed from memory, not at the time of list presentation as proposed by accounts based on failure of encoding or tokenization. The reconstructive account is supported by a series of experiments that show a retroactive effect in which report of C1 is enhanced by similarity to C2; a nonword C1 can either interfere with or enhance report of C2, depending on how accurately C1 is encoded; manipulation of reconstructive processes can eliminate or enhance the effect of orthographic similarity; and a bidirectional trade-off in the report of an orthographically similar C1-C2 pair, whereby report of one member compromises report of the other.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".