The truth effect in relation to neuropsychological functioning in traumatic brain injury
Bibliographic record
Abstract
OBJECTIVES: Individuals with traumatic brain injury may have difficulty accepting other viewpoints, but there is not yet a clinical test to measure the readiness with which one accepts new information as true. This study examined the truth effect-the tendency to rate previously seen material as being 'more true' than newly presented material-to explore whether individual differences in the truth effect can be quantified and related to memory or other neuropsychological variables, including brain injury severity. METHODS: Seventy-four individuals being seen for neuropsychological assessment were asked to classify 15 semantic statements as biographical, scientific or historical and were later asked to rate 10 of the previously viewed statements and 10 new statements as either true or false. RESULTS: A truth effect was clearly present in two groups which had gained familiarity with opposite sets of statements. As well, individuals with better immediate verbal memories rated more of the previously seen statements as true. CONCLUSIONS: A verbal encoding factor appears to underlie the truth effect and may explain the difficulties that some TBI patients have in accepting newly presented information as true.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".