Evaluation of a dendroclimatic process-based model (MAIDEN) over the last century using the PAGES2k tree-ring width database
Bibliographic record
Abstract
Trees are one of the main archives to reconstruct the climate of the last millennium at high resolution. The links between tree-ring proxies and climate have usually been estimated on the basis of statistical approaches, assuming linear and stationary relationships. Both assumptions can be inadequate and this issue can be overcome by ecophysiological models such as MAIDEN (Modeling and Analysis In DENdroecology), which simulates tree-ring growth starting from temperature and precipitation daily inputs. A protocol for the application of MAIDEN to potentially any site with tree-ring width data in the extratropical region has been developed in Rezsöhazy et al. (2019) (in review). In this study, the applicability of the model has been tested over the twentieth century using as a test case tree-ring observations from twenty-one Eastern Canadian taiga sites and three European sites. The paper highlights the potential of MAIDEN as a complex mechanistic proxy system model to analyse the links between tree growth and climatic conditions in paleoclimatic applications. Following on from this recent work, MAIDEN is here applied to the PAGES2k tree-ring width database over the last century using the protocol developed in Rezsöhazy et al. (2019) (in review). We show how this larger network allows refining our protocol. We identify the regions and sites where MAIDEN can be successfully applied, as well as estimate the uncertainty associated with the use of MAIDEN for a wide range of sites. Rezsöhazy, J., Goosse, H., Guiot, J., Gennaretti, F., Boucher, E., André, F., and Jonard, M.: Application and evaluation of the dendroclimatic process-based model MAIDEN during the last century in Canada and Europe, Clim. Past Discuss., https://doi.org/10.5194/cp-2019-140, in review, 2019.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".