P-588 - Scientific profiles of bipolar disorder in web of science (2006–2010)
Bibliographic record
Abstract
Bipolar disorder is a major affective disorder marked by severe mood swings and a tendency to remission and recurrence. It is mainly a biological disorder that occurs in a specific area of the brain that is related to the malfunction of certain neurotransmitters, or chemical messengers, in the brain. The objective of this study is to analyze the scientific activities in the field of Bipolar Disorder by leading countries during a period of 5 years (2006–2010). The database of Science Citation Index-Expanded and Social Science Citation Index were used to extract all data. The study showed that a total number of 11,313 scientific publications were indexed in SCIE and SSCI in the field of Bipolar Disorder during the period of study. The USA sharing 47.5% of world publications was the most productive country followed by England 9.9%, Canada 7.6% and Germany 6.8%. English consisting of 96.2% of total publications language was the most dominant language of publications, followed by French (1.1%), German 1.1% and Turkish 0.5%. Journal Articles consisting of 58% of total publication types was the most frequented publications type. The Journal of “BIPOLAR DISORDERS” publishing 11.6% of world papers was the most prolific journal followed by “BIOLOGICAL PSYCHIATRY” 5%, “JOURNAL OF AFFECTIVE DISORDERS” 5% and “JOURNAL OF CLINICAL PSYCHIATRY” 2.9%. Analysis of data indicated that the most majority of scientific output in the field of Bipolar Disorder came from North America and Western Europe. The USA sharing 47.5% of world knowledge is the leading country.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.017 | 0.030 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".