A PAIN supplement commemorating the 50th anniversary of the International Association for the Study of Pain
Bibliographic record
Abstract
The International Association for the Study of Pain (IASP) will celebrate its 50th Anniversary in 2024. As the current Editor-in-Chief of PAIN (K.D.D.) and Guest Editor (B.J.S.), we are delighted to bring you this special issue containing a series of articles highlighting the activities and achievements of the IASP over this 50-year period. A timeline of events, milestones, and historical materials is also available on the IASP website (see https://www.iasp-pain.org/50th-anniversary/). The IASP was established in 1974 with the mission “to bring together scientists, clinicians, health-care providers, and policymakers to stimulate and support the study of pain and to translate that knowledge into improved pain relief worldwide” (see https://www.iasp-pain.org/about/). A year after its formation, the IASP then created a forum for the dissemination and discussion of high-quality pain research, through the establishment of this journal, PAIN. Thus, it is fitting for the journal to present this special issue of articles that consider not only the wide range of IASP's activities and achievements from the past to the present but also what its journey may look like going forward into the future. The issue starts with an article providing a brief historical overview of some noteworthy IASP events and activities over the past 50 years, including those that led to the establishment of IASP in 1974 and its growth and development over the next 5 decades. This is followed by a series of articles that highlight the myriad of IASP initiatives and activities pertaining to educational, research, and clinical advances, evolving concepts and new technologies and approaches, pain advocacy globally, and publications. Perspectives from IASP trainees and early career members and members from developing countries are also presented, and the issue concludes with an article providing some thoughts on the IASP's next 50 years. The authors of these articles come from a diversity of disciplines and geographic regions (including more than a dozen different countries) and include well-established investigators and clinicians as well as persons with lived experience of pain, trainees, and early career IASP members who collectively reflect the multidisciplinary nature of the IASP membership. Thus, this special issue of PAIN provides an overview of the contributions that the IASP has made and will continue to make in the future regarding pain education, research, management, and advocacy, and its value to IASP members from around the world and to patients who suffer from acute or chronic pain.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.108 | 0.051 |
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".