Adding a new dimension to investigations of early radiolarian evolution
Bibliographic record
Abstract
Knowledge of the detailed architecture of the earliest radiolarian microfossils is key to resolving the evolution and systematics of this important group of marine protozoans. Non-destructive methods for observing the complexity within the internal structures of their siliceous skeletons have long eluded paleontologists. By developing methodologies that overcome some limitations of existing micro-computed tomography (micro-CT) we demonstrate a technique with potential to provide new insight into their evolution. Using 3D micro-CT data to generate models for six well-preserved siliceous radiolarian skeletons from the Middle Cambrian Inca Formation in far north Queensland, Australia and the Middle Ordovician Piccadilly Formation, in western Newfoundland, Canada, we can reconstruct phylogenetic relationships amongst some of the earliest radiolarians. Better knowledge of early radiolarian morphologies clarifies the vital function of internal structures and hierarchical diagnosis across a range of taxonomic affiliations.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".