Report on “Neuropsychoanalysis around the world,” an online meeting hosted by the International Neuropsychoanalysis Society, July 2020
Bibliographic record
Abstract
The 21st Congress of the International Neuropsychoanalysis Society was scheduled to happen on July 9th to 11th in San Juan, Puerto Rico. The coronavirus pandemic led to postponing the event for 2021 and left the Society without its annual meeting. As the world quickly moved on to online communications, the organizing committee decided to have an event in lieu of the Congress on July 11th and 12th. It was titled “Neuropsychoanalysis around the world” and it saw a large audience (approximately 357 people) from all over the world, including Lithuania, Brazil, Argentina, the United States, the United Kingdom, France, Israel, Colombia, Canada, Australia, Germany, Austria, Italy, Uruguay, Turkey, Sweden, Puerto Rico, Spain, Japan, South Africa, Belgium, Chile, Finland, Greece, Ireland, Latvia, the Netherlands, Peru, Norway, Portugal, Switzerland, Ukraine and Mexico. Updates in research, clinical advances, and theory were presented to be followed by comments and discussions from attendees.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.032 |
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".