Characterization of deep-sea benthic invertebrate megafauna of the Galapagos Islands
Bibliographic record
Abstract
The deep sea represents the largest and least explored biome on the planet. Despite the iconic status of the Galapagos Islands and being considered one of the most pristine locations on earth, the deep-sea benthic ecosystems of the archipelago are virtually unexplored in comparison to their shallow-water counterparts. In 2015, we embarked on a multi-disciplinary scientific expedition to conduct the first systematic characterization of deep-sea benthic invertebrate communities of the Galapagos, across a range of habitats. We explored seven sites to depths of over 3,300 m using a two-part Remotely Operated Vehicle (ROV) system aboard the E/V Nautilus, and collected 90 biological specimens that were preserved and sent to experts around the world for analysis. Of those, 30 taxa were determined to be undescribed and new to science, including members of five new genera (2 sponges and 3 cnidarians). We also systematically analysed image frame grabs from over 85 h of ROV footage to investigate patterns of species diversity and document the presence of a range of underwater communities between depths of 290 and 3,373 m, including cold-water coral communities, extensive glass sponge and octocoral gardens, and soft-sediment faunal communities. This characterization of Galapagos deep-sea benthic invertebrate megafauna across a range of ecosystems represents a first step to study future changes that may result from anthropogenic impacts to the planet's climate and oceans, and informed the creation of fully protected deep-water areas in the Galapagos Marine Reserve that may help preserve these unique communities in our changing planet.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".