Meningkatkan Keterampilan Menyimak Isi Teks Cerita Rakyat Melalui Model Pembelajran Snowball Throwing Kelas VC SDN Kesatrian 1 Kota Malang
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Autopsy studies of Alzheimer's disease (AD) have found that neurofibrillary tangle (NFT) pathology of the medial temporal lobe (MTL) demonstrates selective topography with relatively stereotyped subregional involvement at early disease stages, prompting interest in more granular measurement of these structures with in vivo magnetic resonance imaging. We applied a novel, automated method for measurement of hippocampal subfields and extrahippocampal MTL cortical regions. The cohort included cognitively normal (CN) adults (n = 86), early mild cognitive impairment (n = 43), late MCI (n = 22), and mild AD (n = 40) patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For pseudolongitudinal analysis of the continuum from preclinical to mild AD dementia, the groups were further divided according to amyloid status based on positron emission tomography. Specific subregions associated with the early NFT pathology of AD were more sensitive to preclinical and early prodromal AD than whole hippocampal volume while more diffuse involvement was found in later stages. In particular, BA35, the first region associated with NFT deposition, was the only region to discriminate preclinical AD from amyloid negative cognitively normal adults ("normal aging"). In general, patterns of atrophy in the pseudolongitudinal analysis largely recapitulated Braak staging of NFTs within the MTL.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it