Genome analysis of the rice coral Montipora capitata
Bibliographic record
Abstract
Corals comprise a biomineralizing cnidarian, dinoflagellate algal symbionts, and associated microbiome of prokaryotes and viruses. Ongoing efforts to conserve coral reefs by identifying the major stress response pathways and thereby laying the foundation to select resistant genotypes rely on a robust genomic foundation. Here we generated and analyzed a high quality long-read based ~886 Mbp nuclear genome assembly and transcriptome data from the dominant rice coral, Montipora capitata from Hawai'i. Our work provides insights into the architecture of coral genomes and shows how they differ in size and gene inventory, putatively due to population size variation. We describe a recent example of foreign gene acquisition via a bacterial gene transfer agent and illustrate the major pathways of stress response that can be used to predict regulatory components of the transcriptional networks in M. capitata. These genomic resources provide insights into the adaptive potential of these sessile, long-lived species in both natural and human influenced environments and facilitate functional and population genomic studies aimed at Hawaiian reef restoration and conservation.
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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 | 0.000 | 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) | 0.000 | 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".