Bibliographic record
Abstract
Although paleosols are useful indicators of paleoclimates. it is first necessary to establish the relationships between the northern limits of the various contemporary soils and the pertinent climatic parameters. It is then necessary to determine the age of the various paleosols and, if possible, their northern limits. Comparison of the distribution and northern limits of the contemporary soils with the distribution and northern limits of the analogous paleosols then permits the reconstruction of the paleoenvironments. For the purposes of comparison the mean annual temperature of the Old Crow area during the Pliocene epoch was also determined (about 4°C) even though this was not an interglacial period. It was found that during the pre-lllinoian interglacial periods the central Yukon had a mean annual temperature of about 7°C while during the Sangamonian interglacial period it had a mean annual temperature of about - 3°C. During the Holocene epoch, the current interglacial period, the climate has been similar to or only slightly cooler than that existing during the Sangamonian interglacial period. The fluctuating position of the arctic tree line (and associated forest soils) during the Holocene epoch, however, indicates that the climate has also been fluctuating during this time. The paleoclimatic reconstruction presented in this paper also relies heavily on both diagnostic soil features and the soil development during the various interglacial periods.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".