Bibliographic record
Abstract
Evaluation of: Quaranta D, Marra C, Zinno M et al. Presentation and validation of the Multiple Sclerosis Depression Rating Scale: a test specifically devised to investigate affective disorders in multiple sclerosis patients. Clin. Neuropsychol. 26(4), 571–587 (2012).Depression is a troublesome issue in the lives of people with multiple sclerosis (MS). However, there are many questions about how to measure depression in people with MS. Depression is a syndrome that is characterized by emotional, cognitive and somatic symptoms. Depression scales are usually designed to cover each of these domains but in MS there is concern that cognitive deficits and somatic symptoms related to the illness itself may inflate depressive symptom scores, potentially leading to false-positive ratings. Such misclassification may consume excessive resources in screening programs due to the triggering of unnecessary clinical assessments. In research, such misclassification could lead to bias. In an effort to address these issues, the authors of the article under evaluation have recently developed a new scale, the Multiple Sclerosis Depression Rating Scale.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".