Traditional Fishing Methods of Bhutan
Bibliographic record
Abstract
Traditional fishing techniques, practiced in all parts of Bhutan, are described and compared with techniques reported from Nepal. While a wide range of techniques is found in Bhutan, the number is significantly smaller than that from Nepal. For example, six kinds of net are reported from Nepal, but only one from Bhutan. However, the difference in number may reflect in part the limited scope of the present study. At the same time, several techniques appear unique to Bhutan, and others, while similar to their Nepali equivalents, use different materials - plant-derived poisons are an example. Some techniques may have been brought by ancient immigrants from Tibet, with more recent introductions from lowland India and, most recently, from Nepal. DOI: http://dx.doi.org/10.3126/jowe.v6i0.6081 J Wet Eco 2012 (6): 25-30
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".