Historical insights on nearly 130 years of research on Paleozoic radiolarians
Bibliographic record
Abstract
This paper summarizes and highlights the history of descriptive genus-level taxonomy on Paleozoic radiolarians grouped in five major phases: 1) initial discoveries in the 1890s; 2) ignored during the first half of the 1900s; 3) renewed interest during the 1950s to 1970s; 4) the “fast” years of the late 1970s to 1990s; and 5) the early 21st century quest for the oldest and significant progress in the late Permian. In the 1890s, radiolarians were identified with certainty by Hinde in Ordovician radiolarian cherts. Following Hinde's great discovery, and after a 50-year dormant period, Deflandre revived the study of Paleozoic radiolarians through his groundbreaking study of Albaillella from Carboniferous phosphatic nodules, combined with his genius for understanding evolutionary implications. Additional important work was conducted in this third phase by Foreman, particularly with respect to the description of the radiolarian internal structures based on material extracted from Devonian carbonate nodules. The late 1970s saw an expansion in studies that made extensive use of the SEM for the description of Paleozoic radiolarians, many of which had been extracted from chert using HF methods. The potential of radiolarians to unveil the structure and geodynamic evolution of Paleozoic orogenic belts stimulated taxonomic interest during the 1980s and 1990s, a prerequisite for the elaboration of radiolarian biostratigraphic schemes, which was successfully achieved for the upper Paleozoic. The fifth phase follows the discovery of well-preserved Middle Cambrian radiolarians from Australia at the end of the 20th century and subsequent description by Won of beautifully preserved Cambrian and Ordovician fauna from western Newfoundland. Research on early Paleozoic radiolarians was the main driver for the increase of the number of new genera for the last two decades.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".