Reef environments of Murciélago Islands and Santa Elena peninsula, Guanacaste conservation area, Costa Rican pacific
Bibliographic record
Abstract
The ecology of the marine environments of the Murciélago Islands and the Santa Elena Peninsula have been studied little despite their high biodiversity. This area is influenced by a coastal upwelling. In 2014, 2016 and 2018, the region was visited to assess the composition and diversity of its reef environments. Bottom coverage, macroinvertebrate diversity and abundance, and reef fish biomass were quantified. The substrate was dominated by turf and crustose calcareous algae. Live coral coverage has decreased compared to previous reports for the area. Sea urchins were the macroinvertebrates with the highest densities, while species of commercial interest presented low densities, this may suggest some degree of fishing pressure. 84 reef fish species were identified, making the islands area with the greatest diversity of reef fish in the North Pacific of Costa Rica. Coral biotopes in this region are key to the conservation of connectivity between reef areas due to their high diversity.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".