Plants in movement – Floristic and climatic characterization of the New Jersey hinterland during the Palaeogene–Neogene transition in relation to major glaciation events
Bibliographic record
Abstract
Abstract. Mid-Oligocene to Early Miocene terrestrial palynomorphs from the New Jersey hinterland (eastern North America: IODP-Expedition 313) were analysed, using light microscopy and scanning electron microscopy, to infer altitudinal spatial and long-term temporal vegetation migration in context of global climate change. The mesophytic forest was the most widespread vegetation type in the hinterland, with Quercus (Group Quercus, Quercus/Lobatae and aff. Group Protobalanus) being the dominant taxon. Pollen grains of the extinct genus Eotrigonobalanus (Fagaceae) are documented. To infer possible topographic palaeovegetation movements during the selected time interval terrestrial palynomorphs were assigned to six vegetation units. Relative abundances of vegetation units show weak temporal and spatial fluctuations, with the sum of bisaccate pollen grains being most pronounced. Periodic changes in vegetation units suggest movements of the plant cover responding to orbital-scale glacial-interglacial changes of the Oligocene and early Miocene. Relative abundances of several taxa (e.g. Carya) did not change significantly during the Oligocene, but alterations are recognizable when compared with an already published late Middle Miocene record from the same area, probably indicating biotic responds to environment change. A pollen-based bioclimatic analysis with four standard parameters (mean annual temperature, mean temperatures of the coldest and warmest month, mean annual precipitation) was performed to reconstruct palaeoclimatic changes indicating weak fluctuations in temperature and precipitation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".