Bibliographic record
Abstract
In their study,1 McGough and colleagues demonstrated that both usual gait speed and Timed “Up & Go” Test performance was significantly associated with executive functions, after accounting for age, sex, depressive symptoms, medical comorbidity, and body mass index, in a group of sedentary older adults with memory-based mild cognitive impairment (MCI). Their study highlights the co-occurrence of cognitive and physical decline in the clinical condition of MCI and reminds all of us of the complexity of geriatric rehabilitation. Mild cognitive impairment is a well-recognized risk factor for both dementia2 and functional dependence.3,4 It is distinct from dementia and is conceptually defined as a clinical entity that is characterized by cognitive decline greater than that expected for an individual's age and education level but that does not notably interfere with activities of daily living.2,5 It should be noted that MCI exists across a cognitive continuum with borders that are difficult to define precisely.2 Furthermore, there is considerable etiological and clinical heterogeneity within MCI. However, given the consequences of MCI, it is an important clinical entity that requires timely recognition and intervention.
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 | 0.008 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.073 | 0.047 |
| Insufficient payload (model declined to judge) | 0.020 | 0.019 |
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".