International Review Panel Report for the 2005 International Fisheries Stock Assessment workshop
Bibliographic record
Abstract
The Workshop focused on the South African West and South Coast Rock Lobster resources, and also included a session to discuss elephant metapopulation modelling being undertaken by Dr Rudi van Aarde and colleagues at the University of Pretoria. The Workshop was funded jointly by the Marine and Coastal Management Branch of the Department of Environment Affairs and Tourism, the National Research Foundation (through a research grant to D S Butterworth), and the local industry associations for the South African West and South Coast rock lobster fisheries. An External Review Panel of four invited scientists participated in the Workshop. These were Tony Smith (Australia) who chaired the event, Ana Parma (Argentina), Andre Punt (USA) and Paul Starr (Canada and New Zealand). In total, some 30 scientists and industry members attended throughout the event, and about another 40 occasionally. This report does not cover all the discussions that took place. Instead it is comprised of four primary Annexes related to key elements of these discussions.
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 | 0.036 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.049 | 0.015 |
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".