Bibliographic record
Abstract
To the Editor, Many family physicians experience that patients with mental health problems often complain of somatic symptoms. Evidence suggests that depression and anxiety have a significant relationship with somatic symptoms (1). With great interest, I read the article of Dahli et al. about the associations between common psychological diagnoses and somatic symptoms (2). In the 1-year retrospective cohort study including electronic medical data from 15 750 patients aged 16–65 years in Norwegian urban general practice, they investigated associations between stress-related diagnoses, in addition to anxiety- and depression-related diagnoses, and somatic symptoms. Stress-related diagnoses included acute stress and post-traumatic stress disorder. Norway adopts a government-aided tariff system in general practice consultations, and each contact requires a diagnostic code, the International Classification of Primary Care, 2nd edition (ICPC-2), to get reimbursed. The ICPC-2 allows for the coding of social problems, which could bring patients visiting family physicians....
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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.024 | 0.028 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".