Temperature-based variation of rRNA secondary structure models: a case study in the insect<i>Drosophila simulans</i>, the land snail<i>Isabellaria adriani</i>, and the crustacean<i>Daphnia pulex</i>
Bibliographic record
Abstract
The influence of a temperature default on ribosomal RNA (rRNA) secondary structure models was studied with the "Mfold" energy-optimization program. Folding models of the internal transcribed spacer (ITS) 1 rRNA for both Drosophila simulans (Insecta) and Isabellaria adriani (Gastropoda) were generated at two different temperatures. The folding models are compared with the models previously shown for the ITS-1 of D. melanogaster Oregon R strain and I. adriani. A search for phylogenetically informative ITS-1 folding motifs was conducted for D. simulans. In I. adriani, a new approach for ITS-1 secondary structure analyses is suggested. The paper also elucidates results inferred from three energy-optimizing programs (Mfold, GeneBee, and STAR). These three folding programs give different information on the structure and free energy of a ITS-1 rRNA molecule. Furthermore, secondary-structure models of the small subunit (ssu) rRNA of Daphnia pulex (Crustacea: Cladocera) were investigated. The ssu rRNA molecule is usually folded according to alignment information. Here, ssu folding patterns are computed with Mfold using two temperature conditions. The two Mfold models are compared with the alignment model previously suggested for D. pulex. Three cladoceran-specific motifs and a short stem motif within the ssu rRNA of eukaryotes are discussed with respect to structure and phylogenetic information.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".