Bibliographic record
Abstract
A 65-year-old technical worker with previous management function had been unable to work because of pulmonary problems for 7 years. He visited the memory clinic because of slowly progressive memory complaints over the past year, concerning names of familiar people and recent facts. Things get lost and difficulty with multitasking was observed by others. No interference with daily functioning is reported and he denies depressive symptoms. His wife and children confirm memory complaints, but they also noticed changes in behavior. In increasingly common conflict situations the patient sometimes uses verbal and physical violence. There are numerous life events, such as the undesired cessation of work and some other private circumstances, but the patient is reported to show no emotion, while a marked character change is denied by the spouse. General history This highly educated man had been diagnosed with extrinsic allergic alveolitis 7 years ago. He has used prednisolone in the past and now only uses fluticasone inhaler if necessary. Neurologic evaluation 5 years ago, because of black-outs during car driving, revealed no abnormalities. His electroencephalogram (EEG) and magnetic resonance imaging (MRI) were reported to be normal. He stopped smoking 7 years ago and uses three units alcohol daily. Patient lives with his wife and has two children and three grandchildren. Family history The patient’s father suffered from dementia in his 70s and died 8 years after onset of symptoms. No specific diagnosis was made.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".