Inferred summer precipitation for southern Ontario back to AD 610, as reconstructed from ring widths of <i>Thuja occidentalis</i>
Bibliographic record
Abstract
We present a network of seven ring-width chronologies of eastern white-cedar (Thuja occidentalis L.) from the Niagara Escarpment in southern Ontario, Canada. Using principal component regression, a 350-year June-July precipitation reconstruction (SOR) is developed for the region. Prior to the 20th century, the SOR series shows reasonable coherence, particularly at the decadal scale, with an independent tree-ring-based reconstruction of the Palmer drought severity index (PDSI) for roughly the same region. A weakening of the tree-growth climate relationship in recent decades results in a regression model explaining 21% of the variance in the original climate series when the recent data are used for calibration. We therefore compromise with a model, calibrated for the period 19001960, which explains 33% of the variance. The model, while not terribly strong, does pass verification tests, indicating some degree of predictive skill. The longest chronology in our network, the 2787-year Flowerpot Island (FLOW) chronology, also exhibits common variability with the PDSI reconstruction, particularly on decadal and longer time scales and was used to infer hydroclimatic conditions back to AD 610. The combined information of the SOR, PDSI, and FLOW series suggests that dry conditions existed for the periods 17001725, 17501800, and 18401900, and wet conditions for the periods 16751700, 17301750, and 18101840. Over longer time scales, the FLOW chronology shows that summer precipitation was particularly variable during the 7th, 9th, 13th, and 16th centuries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".