Asian geodynamics, climate and biodiversity: an introduction
Bibliographic record
Abstract
This book addresses the interplay between geodynamics, climate and biodiversity, focusing on the India–Asia collision, the key abiotic parameter shaping the region's topography, climate and ecosystems. Asia, with its unparalleled geological activity and rich biodiversity, is ideal for studying interactive processes of Earth system science. Collision shaped the Himalayan and Tibetan Plateau regions, significantly influencing atmospheric circulation, precipitation patterns and biotic evolution. Key questions revolve around the timing and mechanisms of these processes, which remain topics of debate. Fossil records highlight evolutionary patterns, such as plant and animal dispersals during tectonic shifts like the ‘Africa–India Floristic Interchange’. Climatic phenomena, including monsoons and glaciations, further influenced biodiversity by shaping habitats and driving speciation. High-altitude regions, like the Hengduan Mountains, became biodiversity cradles owing to habitat heterogeneity and ecological niches. Advances in tools such as palaeoaltimetry proxies, molecular phylogenetics, climate and landscape modelling clarify the complex interactions between tectonics, climate and biodiversity. Asia's geological history offers vital insights into past climate–biodiversity dynamics that can aid in the prediction of current ecosystem responses to climate change. This region's incomparable geological activity and biodiversity make it a focal point for Earth system science, highlighting the need for interdisciplinary research to address global biodiversity and environmental challenges.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".