Annual report 2001 - North Pacific Marine Science Organization (PICES). Tenth meeting, Victoria, B.C., Canada, October 5-13, 2001
Bibliographic record
Abstract
Report of Opening Session (pdf 42 KB) Report of Governing Council Meeting (pdf 89 KB) Reports of Science Board and Committees: Science Board (pdf 88 KB) Study Group on North Pacific Ecosystem Status Report and Regional Analysis Center Biological Oceanography Committee (pdf 57 KB) Working Group 14: Effective sampling of micronekton Advisory Panel on Marine Birds and Mammals Fishery Science Committee (pdf 37 KB) Working Group 16: Climate change, shifts to fish production, and fisheries management Marine Environmental Quality Committee (pdf 62 KB) Working Group 15: Ecology of Harmful Algal Blooms (HABs) in the North Pacific Physical Oceanography and Climate Committee (pdf 34 KB) Working Group 13: CO2 in the North Pacific Technical Committee on Data Exchange (pdf 24 KB) Implementation Panel on the CCCC Program (pdf 39 KB) BASS Task Team (pdf 32 KB) Advisory Panel on Iron Fertilization Experiment MODEL Task Team (pdf 22 KB) MONITOR Task Team (pdf 32 KB) Advisory Panel on Continuous Plankton Recorder Survey in the North Pacific REX Task Team (pdf 21 KB) Report of the Finance and Administration Committee (pdf 53 KB) List of Participants (pdf 67 KB) List of Acronyms (pdf 13 KB)
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.134 | 0.107 |
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".