Understanding Animal Evolution: The Added Value of Sponge Transcriptomics and Genomics
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
Sponges are important but often-neglected organisms. The absence of classical animal traits (nerves, digestive tract, and muscles) makes sponges challenging for non-specialists to work with and has delayed getting high quality genomic data compared to other invertebrates. Yet analyses of sponge genomes and transcriptomes currently available have radically changed our understanding of animal evolution. Sponges are of prime evolutionary importance as one of the best candidates to form the sister group of all other animals, and genomic data are essential to understand the mechanisms that control animal evolution and diversity. Here we review the most significant outcomes of current genomic and transcriptomic analyses of sponges, and discuss limitations and future directions of sponge transcriptomic and genomic studies.
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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) | 0.001 | 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 it