Evaluation of Suspected Dementia.
Bibliographic record
Abstract
Dementia is a major neurocognitive disorder involving deficits that interfere with daily function. Age is the greatest risk factor for developing the disease. Other risk factors include family history, cardiovascular disease, uncontrolled diabetes, and lower education levels. The initial evaluation for dementia involves recognizing subtle signs that are often missed or mistaken for normal aging. Screening tools include the Mini-Cog, Memory Impairment Screen (MIS), and questionnaires that are completed by caregivers or friends. If cognitive impairment is suspected, a more detailed evaluation should be performed using tools such as the Montreal Cognitive Assessment (MoCA), Saint Louis University Mental Status (SLUMS), or Rowland Universal Dementia Assessment Scale (RUDAS). A thorough history should be taken and a medication review and physical examination should be performed for the assessment of vision; hearing; cardiovascular, nutritional, and functional status; neurologic function; and psychiatric status. Laboratory testing, such as vitamin B12 and folate levels, thyroid function, complete blood cell count, and comprehensive metabolic panel, may be necessary to rule out underlying conditions. Brain imaging with noncontrast magnetic resonance imaging (or non-contrast computed tomography of the head if magnetic resonance imaging is unavailable or contraindicated) can rule out secondary causes. Differentiating dementia from potentially reversible conditions such as depression and delirium is essential. Referral to a neurologist is recommended for early-onset symptoms (before 60 years of age), for severe behavioral disturbances, or if the diagnosis is unclear.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".