Otolith research and application: current directions in innovation and implementation
Bibliographic record
Abstract
The Third International Symposium on Fish Otolith Research and Application was held in Townsville, Queensland, Australia from 11 to 16 July 2004. The overall theme was ‘Innovation and Implementation’, a collection of which is published here (Volume 56, Issue 5). Although age and growth studies predominated at the Symposium, new areas of quality-control assurance, annual-increment formation in deep-sea and tropical fish, image analysis and two-dimensional feature extraction were demonstrated. New statistical approaches were also evident, particularly in the subsampling of commercial data for estimating age compositions. The chemical composition of otoliths as natural data loggers has greatly advanced since the 1998 Symposium, with the advent of micromilling machines, new instrumentation and the use of isotopes rather than elements as environmental indicators. Otoliths will continue to support modern environmental needs for fisheries, marine park assessment, metapopulation conservation and the management of stocks and biodiversity of fish.
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 | 0.138 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.011 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 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".