Biogeographic relationships among deep-sea hydrothermal vent faunas at global scale
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The discovery of deep-sea hydrothermal vent fauna, kilometers deep in the oceans, is a great achievement of 20th-century marine biology. The deep-sea hydrothermal food web does not directly depend on the sun energy. Vent communities rely primarily on trophic associations between chemoautotrophic bacteria and consumers. A small number of endemic taxa are adapted to this highly toxic environment distributed along ridge crests. Where they appeared and how they dispersed is among the important questions ecologists must answer. Here, by statistical analysis of the most comprehensive data base ever assembled about deep-sea hydrothermal fauna, we delineate six major hydrothermal provinces in the World Ocean, then we identify five significant dispersal flows between adjacent provinces and derive a hypothesis about the center from which that fauna has dispersed to the oceanic ridges of the world. Our data-driven conclusion can be tested by phylogenetic studies and completed by surveys of less explored fields.
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.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it