Addiction Medicine in the Time of Covid-19: An Overview of the 2020 Joint Scientific Annual Conference of the International Society of Addiction Medicine and Canadian Society of Addiction Medicine
Bibliographic record
Abstract
has annually published a communication regarding the annual conference of the International Society of Addiction Medicine (ISAM). These pieces have highlighted the important events of the conference and the work of the organization, as reflected in part by selected abstracts from the conference. This editorial communicates the events of the 2020 conference, the third to be held in conjunction with the Canadian Society of Addiction Medicine (CSAM) and the first virtual conference. The conference was attended by over 800 participants and covered a wide range of topics, including addiction medicine during the COVID-19 pandemic. Despite the challenges of not being able to meet physically in Victoria, British Columbia as had been planned, the virtual event provided an opportunity to share current information in order to help advance prevention, treatment, policy and public helath efforts relating to addressing addictions and helping those impacted by these often devastating conditions.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".