P3‐227: Sensitivity of a computerized test to aphasia: The sentence production subtest from cognitive testing on computer (C‐TOC)
Bibliographic record
Abstract
Language is assessed in few computerized batteries for the evaluation of early dementia. Batteries that include a language test fail to assess spontaneous speech production and comprehension. Yet, deficits in these functions can be the earliest presenting symptoms in Frontotemporal dementia (FTD) and Alzheimer Disease (AD). We designed Sentence Production (SP) as a subtest for our new computerized battery, Cognitive Testing on Computer (C-TOC), with the aim of simulating as closely as possible on computer the production of speech. In this study we tested SP's sensitivity to speech and language difficulties characteristic of aphasia syndromes. C-TOC was designed to combine a highly usable test platform with valid test paradigms in the detection of dementia prodromes. C-TOC records clicking-and-moving mouse responses, and therefore allows for the assessment of productive behaviours. The SP subtest requires the description of pictures by selecting words from an array that includes phonemic and semantic lures, and by ordering the selected words into sentences on the screen. For two items, the production of non-canonical sentence structures is forced. SP is scored for semantic units, phrases, word count, time per word, and syntax. The entire C-TOC battery including SP, and neuropsychological tests (NPT) of language were given to subjects with aphasia and cognitively normal controls. Participants included 9 subjects with aphasia, M age=66, SD=11.1; 4 females/5 males, and a mix of etiologies: 5 FTD (1 behavioural-variant, 4 semantic dementia), 1 AD and 3 stroke, and 12 cognitively normal controls, M age=67.5, SD=6.6, 6 females/6 males. As a group, subjects with aphasia performed poorly on all SP measures, on the NPT language tests and on other verbal C-TOC subtests. Their performance was near normal on non-verbal C-TOC subtests. Performance differences were larger and overlap with controls smaller, on SP and NPT than on all other measures. SP performance patterns were qualitatively different for aphasia related to semantic dementia and stroke. The computerized sentence production paradigm that is part of the C-TOC battery is sensitive to a number of aphasia deficits. The paradigm may have utility in screening for different dementia prodromes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".