False recognition of instruction-set lures
Bibliographic record
Abstract
False remembering has been examined using a variety of procedures, including the Deese-Roediger-McDermott procedure, the false fame procedure and the two-list recognition procedure. We present six experiments in a different empirical framework examining false recognition of words included in the experimental instructions (instruction-set lures). The data show that participants' false alarm rate to instruction-set lures was twice their false alarm rate to standard lures. That result was statistically robust even when (1) the relative strength of targets to instruction-set lures was increased, (2) participants were warned about the instruction-set lures, (3) the instruction-set lures were camouflaged in the study instructions and (4) the instruction-set lures were presented verbally at study but visually at test. False recognition of instruction-set lures was only mitigated when participants were distracted between encountering the instruction-set lures and studying the training list. The results confirm the ease with which recognition succumbs to familiarity and demonstrate the robustness of false recognition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".