Bibliographic record
Abstract
Growing interest in past environmental conditions and the need to obtain a long-term perspective on environmental change is leading to increasing use of high-resolution lake sediment records to obtain the clearest indication of past changes. Varved sediments are particularly important for high-resolution studies because they provide a clear, simple means of identifying one year of deposition within along sedimentary sequence. The simple, consistent time increment found in varved sequences provides an unparalleled framework for reconstructing and documenting detailed changes in long term environmental conditions, ranging from hundreds to more than ten thousand years into the past. Additionally, varves can be composed of a variety of materials (biological, chemical, mineral) and are found in a wide range of environments. Therefore, varve-based sedimentary records have applications in a diverse range of paleoenvironmental research fields and study locations. Varves have played a prominent role in numerous geological studies in northern Europe and North America that began in the latter half of the century. Although varved clay deposits were documented in Sweden as early as 1855, it was the linkage between the varves and glacial theories that led the Swedish geologist Gerald De Geer to suggest that varves represented a one-year cycle of deposition. This was largely based on the similarity between the structure of varves and tree rings (Brunnberg, 1995). De Geer suggested that the silt layer represented deposition during the melt season and the clay layer was produced during the cold season under lake ice. By making use of the extensive outcrops of varves found in southern Sweden, De Geer (1912) pioneered the use of varves as a chronological tool to estimate the age of ice retreat. In this and subsequent work, De Geer and other workers measured varve sequences to construct varve thickness chronologies from various locations. These chronologies were correlated to develop a single varve time scale of the postglacial period. This work provided a foundation for future varve work by linking together isolated “floating” chronologies using distinctive marker varves found at multiple sites (De Geer 1912, 1934). Similar to the process routinely used in dendrochronology (Fritts, 1976),
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.018 |
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".