Fifty years of IAHR’s Symposium on Ice: country contributions and international co-authorship
Bibliographic record
Abstract
The first edition of IAHR’s international Symposium on Ice, then called Ice Problems in Hydraulic Structures, was held in Reykjavík in 1970, and mostly on a biennial basis thereafter. The topics that were addressed during these 50 years were mainly on ice engineering, both in freshwater and saline water environments. River ice, ice mechanics, ice forces and ice interaction with structures were usually included. The impact of climate change as a topic appeared in the early 1990’s, while input related with ecology, water quality and impacts of oil spills began in the late 1990’s. Some of the proceedings included the outcome of several working groups on topical issues such as ice force, hydraulics and modeling. The number of records (papers, keynote addresses and posters) from all 25 sets of proceedings totaled 2599, by authors from 37 countries. An analysis of country-per-country contributions was done on that corpus – it showed that Canada, USA, USSR/Russia and China are the overall top contributors. Norway’s input gradually increased to take the lead, with almost 30% of all output for the 2020 edition. The analysis conducted herein showed that the level of international coauthorship, which was assessed using a simple index devised for that purpose, has been on the rise, from 0% in 1970 to 47% in 2020.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.043 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".