Assessment of semantic memory in mild cognitive impairment: The psychometric properties of a novel semantic battery
Bibliographic record
Abstract
Semantic memory is stable in healthy older adults but shows decline in mild cognitive impairment (MCI). Current measures of semantic function do not assess multiple aspects of semantic function and/or are time-consuming to administer. Here we report the psychometric properties of a battery to detect semantic impairment that we recently developed and published. Study 1 determined the face validity of the battery; interviews were conducted with five professionals with expertise in MCI and language. Face validity interviews suggested the battery appropriately assesses semantic impairments. Study 2 assessed convergent validity and reliability (inter-rater reliability, test-retest reliability, and internal consistency). Participants included 102 healthy older adults and 60 people with MCI who completed a four-task semantic battery. Results demonstrate that performance on the semantic battery correlates with traditional measures of semantic function, inter-rater reliability and internal consistency was high, and there was no significant change in mean scores between participants' first and second testing sessions. The present findings suggest that the semantic battery is a reliable and valid assessment of semantic function. It is currently recommended for research use only.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".