Bibliographic record
Abstract
The supercontinent cycle, by which Earth history is seen as having been punctuated by the episodic assembly and breakup of supercontinents, has influenced the rock record more than any other geologic phenomena, and its recognition is arguably the most important advance in Earth Science since plate tectonics. It documents fundamental aspects of the planet's interior dynamics and has charted the course of Earth's tectonic, climatic and biogeochemical evolution for billions of years. But while the widespread realization of the importance of supercontinents in Earth history is a relatively recent development, the supercontinent cycle was first proposed thirty years ago and episodicity in tectonic processes was recognized long before plate tectonics provided a potential explanation for its occurrence. With interest in the supercontinent cycle gaining momentum and the literature expanding rapidly, it is instructive to recall the historical context from which the concept developed. Here we examine the supercontinent cycle from this perspective by tracing its development from the early recognition of long-term episodicity in tectonic processes, through the identification of tectonic cycles following the advent of plate tectonics, to the first realization that these phenomena were the manifestation of episodic supercontinent assembly and breakup.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".