<i>Biological Bulletin</i> Virtual Symposium: Genomics of Large Marine Metazoans
Bibliographic record
Abstract
The phrase “genomics of large marine metazoans” is an ungainly mouthful. So are the animals themselves, in most cases. The species addressed in this virtual symposium circumscribe a great catalog of morphological, ecological, and phylogenetic diversity that has fascinated marine scientists for many years. Genome sequences and expressed sequence tag projects provide a means to understand this diversity from a different and in some ways more comprehensive viewpoint. Collectively the animals that are the subject of these papers differ significantly from the standard genetic models that dominate our current understanding of the breadth of animal molecular biology. These differences are reflected in their life history and larger genomes (though by no means unusually large). Their longer life spans may correlate with their often greater genetic complexity. Finally, the marine environment compasses extreme ranges of physical conditions, and understanding the unique genetic features of extremophiles will be helped tremendously by genomic approaches (see Nyholm et al., this issue).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.222 | 0.058 |
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".