<scp>CO</scp><sub>2</sub> studies remain key to understanding a future world
Bibliographic record
Abstract
Summary Characterizing plant responses to past, present and future changes in atmospheric carbon dioxide concentration ([CO2]) is critical for understanding and predicting the consequences of global change over evolutionary and ecological timescales. Previous CO2 studies have provided great insights into the effects of rising [CO2] on leaf‐level gas exchange, carbohydrate dynamics and plant growth. However, scaling CO2 effects across biological levels, especially in field settings, has proved challenging. Moreover, many questions remain about the fundamental molecular mechanisms driving plant responses to [CO2] and other global change factors. Here we discuss three examples of topics in which significant questions in CO2 research remain unresolved: (1) mechanisms of CO2 effects on plant developmental transitions; (2) implications of rising [CO2] for integrated plant–water dynamics and drought tolerance; and (3) CO2 effects on symbiotic interactions and eco‐evolutionary feedbacks. Addressing these and other key questions in CO2 research will require collaborations across scientific disciplines and new approaches that link molecular mechanisms to complex physiological and ecological interactions across spatiotemporal scales. Contents Summary 34 I. Introduction 34 II. CO2 effects on plant development and phenology 36 III. CO2 effects on plant–water dynamics 37 IV. CO2 effects on plant–microbe interactions 37 V. The way forward 38 Acknowledgements 38 References 38
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".