Spelberoende är en högaktuell diagnos - Snabba internetspel om pengar har stor beroendepotential – KBT ger god effekt
Bibliographic record
Abstract
Gambling disorder is a serious condition and a current issue in Sweden. The national prevalence of problem gambling is 2 %, including 0.4 % meeting criteria for gambling disorder, but the incidence numbers are substantially higher due to the dynamic pattern of the disorder with people moving into and out of the problem gambling group. Rapid internet games, such as internet casinos and sports betting, cause a predominant share of the gambling problems, and the market has shown an unrestrained growth for years. New public amendments are upcoming and from the 1st of January 2018, healthcare and social services have a pronounced obligation to offer investigations and treatment (mainly CBT) for gambling disorder. The psychiatric comorbidity is high, and the risk of suicide is clearly elevated among people with gambling disorder. There are quick, evidence-based screening tools that can easily be used in clinical work, as initial steps of investigations. The need for implementing effective national strategies and further research in the area is considerable.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.036 |
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".