Bibliographic record
Abstract
A recent issue of the journal Science, marking it's 125 th anniversary, has been devoted to 125 questions: What don't we know?".One of the questions addressed the relevance of genetic variation to personal health, acknowledging that genetic dissection of diseases such as cancer, asthma and heart disease is galloping ahead, whereas progress in other disorders such as depression is much slower.Evaluating physical, social and mental impacts of disease, depression was the fourth leading cause on the Global Burden of Illness list in 1990 and is predicted to be the number ONE leading cause in the year 2020.The morbidity associated with depression in women is even greater.Not only do twice as many women suffer from the disorder when compared to men, but they also have a higher rate of comorbid conditions, both physical and mental.From the age of menarche until well after menopause women also suffer from specific mood disorders including premenstrual dysphoria, perinatal and perimenopausal depression, as well as mood and anxiety disorders associated with infertility and pregnancy loss.Women endure more eating disorders, generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and autoimmune diseases.Women are also less tolerant to alcohol use and have a higher prevalence of pain disorders.They are influenced to a greater degree by seasonality, suffer more from jet lag and from shift-work, and last but not least metabolize drugs differently than men.Most of this very valuable information has only been gathered in the last 30 years but much more still needs to be learned.Some of the bigger questions to be answered are obvious: why is it that women are more vulnerable, more at risk to develop these disorders?What causes the sex/gender discrepancy?How can we better identify those who are at risk?What preventative measures can be put in place?And last but not least: how can we "tailor" better female specific treatments/interventions?In addition, the still much-debated question of nature versus nurture seems even more relevant to the higher prevalence of mood and anxiety disorders in women.The evolutionary perspective suggests that possible male-female asymmetries in preference for certain types of relationships, a differential investment in reproduction and childrearing, as well as social options (or the lack of), all contribute to the fact that women are more vulnerable to mood (major depression and dysthymia) as well as anxiety disorders (especially GAD and PTSD).Women are exposed to uncontrollable stressors, both psychological and physical, including violence, abuse and rape, from an early age on, much more often than men.Although such stressful life events may influence the onset and course of depression, GAD and/or PTSD, not all women who encounter stressful situations develop these disorders.It is suggested that an individual's response to environmental insults is moderated by her genetic makeup. 1 Thus, complex psychiatric disorders are probably not caused by genes alone.The hypothesis of a gene-by-environment interaction is very promising.It "accommodates" genetic polymorphism/ vulnerability, environmental pathogens as well as stressful life Editorial Saúde mental da mulher: o que não sabemos?Women's mental health: what don't we know?
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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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.030 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".