Supporting Information for "Conditions to preserve sedimentary record of channel planforms in temperate rivers of the Northern Hemisphere".
Bibliographic record
Abstract
This supplemental material contains three figures and four tables. The figures show an example of a GPR (ground-penetrating radar) image showing how hydraulic radii and cross-sectional areas were estimated for the former channels (fig.S1), GPR images showing the internal structure of anabranching channels and floodplains of the middle Obra (Poland) and Sió Valleys (Hungary) (fig.S2), and aerial images of the South Saskatchewan River (Canada) (fig.S3). The tables show data describing the geometry of channels preserved in ancient rock records (Table S1), results of a statistical test applied to verify whether the values of sinuosities of channels preserved in the top parts of the modern floodplains are statistically different from sinuosities of channels preserved in ancient fluvial records (Table S2), values of manning n coefficients and standard errors (Table S3), estimations of palaeodischarges and standard errors (Tables S4). Data regarding channel geometry, age of former channels, values of Manning hydraulic roughness coefficients, and palaeodischarges were created by Słowik (2013, 2014), and Słowik et al., (2020, 2021). Information about how the values of roughness coefficients, palaeodischarges, and channel belt widths were estimated, and uncertainties of the estimations, are shown in the main body of our paper.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.696 | 0.148 |
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".