Blue Swimming Crab (Portunus pelagicus) Fishery Status in Lianga Bay, Surigao del Sur, Philippines
Bibliographic record
Abstract
This study aimed to determine the catch per unit effort (CPUE), fishing gears used, catch volume, carapace length, and physico-chemical parameters of the Blue Swimming Crab (BSC) in the four municipalities of Lianga Bay, Surigao del Sur, Philippines, namely Barobo, Lianga, San Agustin, and Marihatag. The survey questionnaire was deployed based on the Blue Swimming Crab Management Plan (BSCMP). After three months of observation, Barobo obtained the highest CPUE while Marihatag had the lowest. Barobo also had the highest CPUE using a gill net and crab pot while San Agustin had the lowest using bintol. In terms of catch, the monthly trend showed that March had the highest catch, while April had the least. The frequency distribution of the carapace length showed a unimodal pattern in all municipalities. The physico-chemical parameters of the water were within tolerable limits for the BSC. This study provides baseline data on the BSC fishery in Lianga Bay, which can be used in developing sustainable management strategies for the BSC fishery in the area, ensuring its long-term viability while promoting conservation efforts.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".