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
In the legal field, victims and offenders frequently lie to avoid talking about serious incidents, such as past experiences of sexual abuse or criminal involvement. Although these individuals may initially lie about an experienced event, oftentimes these same people eventually abandon their lies and are forthcoming with what truly happened. To date, it is unclear whether such lying affects later statements about one's memory for the experienced event. The impetus of the present review is to compile the current state of knowledge on the effects of lying on memory. Based on existing literature, we will describe how deceptive strategies (e.g., false denials) regarding what is remembered may affect memory in consequential ways, such as forgetting of details, falsely remembering features that were not present, or a combination of both. It will be argued that the current literature suggests that mnemonic outcome is contingent on the type of lie and we will propose a theoretical framework outlining which forms of lying likely result in certain memory outcomes. Potential avenues of future research also will be discussed.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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