Bibliographic record
Abstract
On examining the scientific literature of recent years, one notices an increase in the number of studies of global warming and its impact on the Earth’s various environments. Research has been undertaken in various fields such as geomorphology, hydrology and many others. In the context of climatic change, there is growing interest in the study of past floods, or palaeofloods. Researchers are attempting to reconstitute the chronology of past floods, especially with respect to past or subrecent climatic changes. The work involves using different methodological approaches borrowed from various disciplines including geology, geomorphology and ecology. The reconstruction of ancient hydrological events such as palaeofloods in fact requires that different methods and techniques be combined in order to trace the chronology of events as precisely as possible using different biophysical parameters. A wide variety of indicators are used in the chronological reconstruction of ancient fluvial environments, whether in humid, subhumid or desert regions. These indicators involve analysing stratigraphic sequences and sedimentary deposits, organic matter and macrorest deposits, as well as using radiocarbon dating( 14 C), thermoluminescence (TL), and dendrochronology and lichenometry. In fact, most work on the reconstitution of the frequency and magnitude of ancient floods uses several methods and techniques to obtain the long-term chronology of flood events in relation to the specific conditions (e.g., climate, geomorphology) of a region or study area. With the publication of several studies in palaeohydrology, it was interesting to examine, through a literature review, the various approaches used in the study of palaeofloods. This kind of study has seen major advances, which can be explained partly by the interest generated by global climate change and its effect on river-system dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".