Epochs, events and episodes: Marking the geological impact of humans
Bibliographic record
Abstract
Event stratigraphy is used to help characterise the Anthropocene as a chronostratigraphic concept, based on analogous deep-time events, for which we provide a novel categorization. Events in stratigraphy are distinct from extensive, time-transgressive ‘episodes’ – such as the global, highly diachronous record of anthropogenic change, termed here an Anthropogenic Modification Episode (AME). Nested within the AME are many geologically correlatable events, the most notable being those of the Great Acceleration Event Array (GAEA). This isochronous array of anthropogenic signals represents brief, unique events evident in geological deposits, e.g.: onset of the radionuclide ‘bomb-spike’; appearance of novel organic chemicals and fuel ash particles; marked changes in patterns of sedimentary deposition, heavy metal contents and carbon/nitrogen isotopic ratios; and ecosystem changes leaving a global fossil record; all around the mid-20th century. The GAEA reflects a fundamental transition of the Earth System to a new state in which many parameters now lie beyond the range of Holocene variability. Globally near-instantaneous events can provide robust primary guides for chronostratigraphic boundaries. Given the intensity, magnitude, planetary significance and global isochroneity of the GAEA, it provides a suitable level for recognition of the base of the Anthropocene as a series/epoch.
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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".