Flood and megaflood processes and deposits : recent and ancient examples
Bibliographic record
Abstract
Preface. 1. MEGAFLOODS. High--energy megafloods: planetary settings and sedimentary dynamics (Victor. R. Baker). Late--Quaternary catastrophic flooding in the Altai Mountains of south--central Siberia: a synoptic overview and an introduction to flood deposit sedimentology (Paul A. Carling, Alistair D. Kirkbride , Sergei Parnachov, Pavel S. Borodavko and Glenn W. Berger). Great Holocene floods along Jokulsa a Fjollum, north Iceland (Richard B. Waitt). 2. GLACIAL OUTWASH FLOODS. November 1996 jokulhlaup on Skeidararsandur outwash plain, Iceland ( rni Snorrason, Pall Jonsson, Or SigurAdegreesson, Svanur Palsson, Sigvaldi rnason, Skuli Vikingsson and Ingibjorg Kaldal). The effects of glacier--outburst flood flow dynamics on ice--contact deposits: November 1996 jokulhlaup, SkeiAdegreeararsandur, Iceland (Andrew J. Russell and Askar Knudsen). Formation of ice--block obstacle marks during the November 1996 glacier--outburst flood (jokulhlaup), SkeiAdegreeararsandur, southern Iceland (Helen Fay). A large--scale flood event in 1994 from the mid--Canterbury Plains, New Zealand, and implications for ancient fluvial deposits (Greg H. Browne). 3. ALLUVIAL--FAN FLOODS. Alluvial--fan sedimentation from a glacial outburst flood, Lone Pine, California, and contrasts with meteorological flood deposits (Terence C. Blair). Alluvial fans in the Italian Alps: sedimentary facies and processes (Andrea Moscariello, L. Marchi , F. Maraga and G. Mortara). Analysis of terrestrial hyperconcentrated flows and their deposits (Marco Benvenuti and I. Peter Martini). Catastrophic debris--flow deposits from an inferred landslide--dam failure, Eocene Berga Formation, eastern Pyrenees, Spain (Eloi Saula, Emili Mato, E. and Cai Puigdefabregas). 4. ALLUVIAL VALLEY FLOODS. Coarse--grained flood bars formed at the confluence of two subarctic rivers affected by hydroelectric dams, Ontario, Canada (Sara--Jane Mosher and I. Peter Martini). Comparison of the flood response of a braided and a meandering river, conditioned by anthropogenic and climatic changes (Guillermina Garzon and A. Alonso). Effects of land--use and precipitation changes on floodplain sedimentation in the 19th And 20th century (Geul River, the Netherlands) (Marleen. H. Stam). Use of remote sensing in monitoring river floods and their effects on the landscape (Lena Halounova). 5. SPECIAL CASES. Sedimentary traces as indicator of temporary ice marginal channels in the Westphalian Bight, Germany (Juergen Herget). Outlet glaciers of the Pleistocene (LGM) south Tibetan ice sheet between Cho Oyu and Shisha Pangma as potential sources of former megafloods (Matthias Kuhle). Index.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".