NOAA/WDS Paleoclimatology - Porter - Schooner Channel Mackenzie Delta - PCGL - ITRDB CANA517
Bibliographic record
Abstract
We present a reconstruction of June-July minimum temperatures since AD 1245 for the Mackenzie Delta region based on a 29-site network of white spruce (Picea glauca) ring-width series. Most but not all trees experienced a divergent temperature-growth response, similar to the divergence that has affected other white spruce trees across Yukon and Alaska. However, divergence in the study region began as early as AD 1900 and we have documented our methods to avoid including divergent signals in the reconstruction. Calibration/verification testing based on local temperature data, and multi-century coherence with nearby and large-scale temperature proxy records, confirm that our reconstruction is robust. The reconstruction shows cool conditions in the late 13th, early 18th and early 19th centuries, corresponding with solar minima and increased volcanism. These cool periods are interrupted by warm periods consistent with early to mid-20th century warmth. The late 20th century is the warmest interval, and the last decade is estimated to be 1.4C warmer than any decade before the mid-20th century. The reconstructed climate history corroborates other proxy-based inferences and supports the notion that high-latitude regions such as the Mackenzie Delta have experienced rapid warming in recent decades that is exceptional in the last eight centuries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".