Phase 4 of PAGES 2k: Hydroclimate of the common era
Bibliographic record
Abstract
<!--!introduction!--> The climate of the past two thousand years (2k) provides context for current and future changes, and as such is vital for developing our understanding of the modern climate system. Previous PAGES 2k network phases emphasized temperature reconstructions, fundamentally improving our understanding of global climate changes over the Common Era. These reconstructions were featured in the Summary for Policymakers of the IPCC’s Sixth Assessment Report. Integration of this data with state-of-the-art Earth systems models, proxy system models and data assimilation yielded a more comprehensive understanding of the associated physical drivers and climate dynamics. Phase 4 of the PAGES 2k Network paves the way for a new level of understanding of the global water cycle. Our aim is to reconstruct hydroclimatic variability over the Common Era, from local to global spatial scales, at sub-annual to multi-centennial time scales, developing a process-level understanding of past hydroclimate events and variability. Our multi-faceted approach includes (1) developing new hydroclimate syntheses that are well-suited for data-model comparisons, (2) improving the interoperability and scope of existing data and model products, and (3) facilitating the translation of our science into evidence-based policy outcomes. In this presentation, we describe the progress to date, and focus the discussion on what a suitable hydroclimate proxy database should look like, both from the perspective of what data are available, and from what is a good target for model evaluation, using different regions of the world as case studies. PAGES 2k is an open community, and you are welcome to get involved.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.018 |
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".