Bibliographic record
Abstract
Abstract This poster session paper reports on research exploring (1) how individuals with early‐stage Alzheimer's disease (AD) use memory cues in the form of representations (tokens) to recall memories of life stories, and (2) ways in which representations (tokens) influence the nature and content of the individual's recall narrative. Further, it examines whether memory recall differs in response to personal, participant‐chosen memory cues, as compared to those selected by someone other than the participant. Reliance on personal artifacts used during two of three unstructured interview sessions resulted in recollections that seemed more scripted in delivery and circumscribed in detail. In contrast, and in response to researcher‐selected tokens used exclusively during session 3, full recollections and additional stories were seen to be more fully formed and detailed. While this subset of a larger study deals only with one individual, findings suggest that generic associations may be at least equal to, if not more effective than, unique, individuated artifacts to engendering creative self‐expression and vivid personal recall for those experiencing the initial memory loss of AD. This finding may open opportunities to cultural heritage institutions (libraries, archives, museums, galleries) to assemble information “memory boxes” that reinforce recall of life stories by clients with early‐stage AD.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".