Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish
Bibliographic record
Abstract
Foreword [pdf, < 0.1 MB] Acknowledgements PHASE 1 [pdf, 0.2 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (July 19–20, 2007, Seattle, U.S.A.) Background Links to Other Programs Workshop Format Session I. Status of climate change scenarios in the PICES region Session II. What are the expected impacts of climate change on regional oceanography and what are some scenarios for these drivers for the next 10 years? Session III. Recruitment forecasting Session IV. What models are out there? How is climate linked to the model? Session V. Assumptions regarding future fishing scenarios and enhancement activities Session VI Where do we go from here? References Appendix 1.1 List of Participants PHASE 2 [pdf, 0.7 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (October 30, 2007, Victoria, Canada) Background Workshop Agenda Forecast Feasibility Format of Information Modeling Approaches Coupled bio-physical models Stock assessment projection models Comparative approaches Similarities in Data Requests Opportunities for Coordination with Other PICES Groups and International Efforts BACKGROUND REPORTS PREPARED FOR THE PHASE 2 WORKSHOP Northern California Current (U.S.) groundfish production by Melissa Haltuch Changes in sablefish (Anoplopoma fimbria) recruitment in relation to oceanographic conditions by Michael J. Schirripa Northern California Current (British Columbia) Pacific cod (Gadus macrocephalus) production by Caihong Fu and Richard Beamish Northern California Current (British Columbia) sablefish (Anoplopoma fimbria) production by Richard Beamish Northern California Current (British Columbia) pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon production by Richard Beamish Northern California Current (British Columbia) ocean shrimp (Pandalus jordani) production by Caihong Fu Alaska salmon production by Anne Hollowed U.S. walleye pollock (Theragra chalcogramma) production in the eastern Bering Sea and Gulf of Alaska by Kevin Bailey and Anne Hollowed U.S. groundfish production in the eastern Bering Sea by Tom Wilderbuer U.S. crab production in the eastern Bering Sea by Gordon H. Kruse Forecasting Japanese commercially exploited species by Shin-ichi Ito, Kazuaki Tadokoro and Yasuhiro Yamanka Russian fish production in the Japan/East Sea by Yury Zuenko, Vladimir Nuzhdin and Natalia Dolganova Chum salmon (Oncorhynchus keta) production in Korea by Sukyung Kang, Suam Kim and Hyunju Seo Jack mackerel (Trachurus japonicus) production in Korea by Jae Bong Lee and Chang-Ik Zhang Chub mackerel (Scomber japonicus) production in Korea by Jae Bong Lee, Sukyung Kang, Suam Kim, Chang-Ik Zhang and Jin Yeong Kim References Appendix 2.1 List of Participants PHASE 3 [pdf, < 0.1 MB] Summary of the PICES Workshop on Linking Global Climate Model Output to (a) Trends in Commercial Species Productivity and (b) Changes in Broader Biological Communities in the World’s Oceans (May 18, 2008, Gijón, Spain) Appendix 3.1 List of Participants Appendix 3.2 Workshop Agenda (Document contains 101 pages)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 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".