The 24th International Seaweed Symposium - ‘Seaweeds in a changing world’
Bibliographic record
Abstract
Abstract The 24th edition of the International Seaweed Symposium (ISS), an academic-industry event that dates back to 1952, was held for the first time in Oceania. The local organizing committee chaired by Professor Catriona Hurd, Institute for Marine and Antarctic Studies, University of Tasmania, and Professor Michael A. Borowitzka, Murdoch University, Western Australia worked tirelessly to curate a program that balanced scientific rigor with engaging discussions, providing ample opportunities for networking and collaboration. “Seaweeds in a changing world” was the theme of this symposium, participants from 48 countries from all over the world attended this symposium from 19-24 February 2023. More than 576 on-site and 207 virtual participants registered for the Symposium who contributed to the success of this event. The International Seaweed Association (ISA) ensures the continued development of seaweed and its benefits and serves as a bridge between research academia and industry. The ISA is ready to celebrate the Silver Jubilee of the ISS and is also proud to announce that the 25th International Seaweed Symposium (ISS) will be held in Victoria, British Columbia, Canada, 4-9 May, 2025 with the Local support of Ocean Networks Canada, Cascadia Seaweed, and the Pacific Seaweed Industry Association ( https://iss25.com ).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.020 |
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".