Use of chemicals in aquaculture in Asia. Proceedings of the Meeting on the Use of Chemicals in Aquaculture in Asia, 20-22 May 1996; Tigbauan, Iloilo, Philippines.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AQUACHEM was funded by the Government of the Philippines through SEAFDEC Aquaculture Department, the Food and Agriculture Organization of the United Nations, and the Canadian International Development Agency through the ASEAN-Canada Fund. Dr. Efren Ed. C. Flores, former Chief of SEAFDEC AQD, laid down the ground-work for the smooth conduct of the meeting as well as solicited funds to support data gathering and travel of some participants from the ASEAN countries. We thank Milagros T. Castanos and Renelle Ivy Y. Adan of the Development Communications Unit, SEAFDEC, who helped in the lay-out of this proceedings.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it