Periodically forced self-organization in the long-term evolution of planktic foraminifera
Bibliographic record
Abstract
Wavelet transform and other signal analysis techniques suggest that the planktic foraminiferal (PF) long-term evolutionary record of the last 127 Ma can be attributed to complex periodic and nonlinear patterns. Correlation of the PF extinction pattern with other geological series favors an origin of the ~30 Ma periodicity and self-organization by quasi-periodic mantle-plume cycles that in turn drive episodic volcanism, CO2-degassing, oceanic anoxic conditions, and sea-level fluctuations. Stationary ~30 Ma periodicity and a weak secular trend of ~100 Ma period are evident in the PF record, even without consideration of the mass extinction at the KT boundary. The 2732 Ma periodicity in the impact crater record and lows in the global sea-level curve, respectively, are ~6.5 Ma and ~2.3 Ma out of phase with PF-extinction data, although major PF-extinction events correspond to the bolide impacts at the KT boundary and in late Eocene. Another six extinction events correspond to abrupt global sea-level falls between the late Albian and early Oligocene. Self-organization in the PF record is characterized by increased radiation rates after major extinction events and a steady number of baseline species. Our computer model of long-term PF evolution replicates this SO pattern. The model consists of output from the logistic map, which is forced at 30 Ma and 100 Ma frequencies. The model has significant correlations with the relative PF-extinction data. In particular, it replicates singularities, such as the KT event, nonstationary 2.510 Ma periodicities, and phase shifts in the ~30 Ma periodicity of the PF record.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".