Mapping permeability over the surface of the Earth
Bibliographic record
Abstract
[1] Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1–2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of ∼5 × 10−14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".