Bibliographic record
Abstract
OBJECTIVES: To review the data that support the role of genetic factors in the predisposition to suicidal behavior and to examine whether or not these factors are part of the genetic liability to mood disorders. To review molecular genetic studies carried out in suicidal behavior. METHODS: A review of the literature was carried out by means of systematic bibliographic database searches and complemented by searches in the references of relevant publications. RESULTS: There is consistent evidence suggesting that genetic factors play an important role in the predisposition to suicide and suicidal behaviors. Although there is important overlap between suicide and mood disorders, a common genetic liability seems unlikely. It is possible that part of the predisposition to suicide may be transmitted via the presence of impulsive and impulsive-aggressive behaviors. An increasing number of molecular genetic studies have been carried out in subjects with suicidal behavior. There is some support for a role of some genes that code for components of the serotonergic pathway in the etiology of suicidal behavior, but these studies are still preliminary. CONCLUSIONS: Further studies are needed at the epidemiological, clinical and molecular level to better characterize the genetics of suicide. These should control for the presence of behaviors that are considered as part of the phenotypic spectrum of suicide.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".