Bibliography of Aquatic Sciences, Fisheries and Aquaculture in Ethiopia
Bibliographic record
Abstract
This Bibliography of Aquatic Sciences, Fisheries and Aquaculture is prepared with the intention of providing the opportunity for different users to easily search for references that concentrate on Aquatic Sciences, Fisheries, and Aquaculture (ASFA). It is a collection of both grey literatures and scientific articles published in scientific journals. The grey pieces of literature include papers presented in conferences, symposia, and workshops, Ph.D. dissertations and MSc theses of various national and international universities submitted as an academic requirement for graduation. It should be noted that there are many more monographs of these types that could be found mainly in different universities in Ethiopia. The scientific papers published in Journals and included in this bibliography should be checked for reputability. As the bibliography contains grey literatures and published papers it can serve as a source of relevant information and data useful for metaanalysis on key topics/issues of ASFA. It will also help the scientific community to enhance their teaching, research and extension activities. Moreover, the long list of references included in the bibliography shows the immense contribution of prominent researchers that promoted, not only their carrier but their profession in the aforementioned three specialized fields. Since the Bibliography is a collection of research reports taken from different sources, there may be a lack of consistency while writing the references. For instance, Ethiopian authors include full father name while writing most of the references, however, abbreviated father name is included whenever the original paper does not have full father name. Finally, it should be noted that this bibliography on ASFA is brought out for the first time in Ethiopia, and we are confident that it will be updated in due course through contributions and feedback from researchers in the field.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.027 | 0.037 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.020 |
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".