Holocene variations in the global hydrological cycle quantified by objective gridding of lake level databases
Bibliographic record
Abstract
Lake level fluctuations provide evidence about past variations in the global hydrological balance. The geostatistical approach is here used to more objectively identify global patterns using an ensemble of lake level databases by examining spatial autocorrelation between sites. The spatial structures of the lake level data are then modeled and grids produced for the last 12,000 years at 3000‐year intervals using ordinary and indicator kriging techniques. The two gridding techniques produced almost identical estimated regional lake status patterns, thus suggesting a robust estimation. The resulting lake‐status grids are in general agreement with previous paleoclimatic reconstructions using only site‐by‐site lake status point maps; however, the reduction of local fine‐scale variability resulted in more coherent regional spatial patterns in areas of high local variability. The 6 ka lake‐status grids were compared to simulations of four atmospheric general circulation models to illustrate their usefulness in validating broad‐scale climate model outputs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".