What the past tells us about the future of Pacific salmon research
Bibliographic record
Abstract
Abstract The Larkin lectures are held every two years at the University of British Columbia in recognition of Dr. Peter Larkin's contributions to fisheries science. The lecture I presented in November 2015 coincided with an announcement that the Institute of Fisheries that Peter Larkin founded in the 1960s would be restructured as the “Institute for Oceans and Fisheries” with an emphasis on fisheries and oceans issues important to British Columbia as well as the rest of the world. I decided to look back at research issues that Peter Larkin thought would be important for Pacific salmon ( Oncorhynchus spp.) in the future and see what has happened as a way of identifying the complexity that the Institute for Oceans and Fisheries in particular and the science community in general will face. I chose five themes from Peter Larkin's talks: 1 understanding marine survival, 2 ocean carrying capacity, 3 aquaculture, 4 climate, Pacific salmon and climate change and 5 informing the public, and then added my opinion about research priorities for the future. Peter Larkin recognized the future relevance of these examples, but he probably could not have imagined how these and related issues will challenge his renamed institute and the rest of the research community over the next 50 years.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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; both teacher heads agree on what is shown here.
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".