Online databases of the geologic formations of Asia and Africa with display onto plate reconstructions
Bibliographic record
Abstract
Building paleogeographic maps that are projected onto different tectonic plate reconstruction models requires team efforts to compile extensive interlinked databases of regional sedimentary and volcanic facies, data sharing standards, and computer projection methods. Two goals of the Deep-Time Digital Earth (DDE) program of the International Union of Geological Sciences (IUGS) Paleogeography Working Group are: (1) to interconnect online national databases for all geologic formations, and to compile these online "lexicons" for countries that currently lack these; (2) to project the combined paleogeographic output of these distributed databases for any time interval onto appropriate plate tectonic reconstructions.Therefore, we have worked with regional experts to compile and interlink cloud-based lexicons for different regions of the world that are enhanced by graphic user-interfaces. Online lexicons with map-based and stratigraphic-column navigation are currently completed for the Indian Plate (ca. 800 formations), China (ca. 3200), Vietnam-Thailand-Malaysia (ca. 600), and all major basins in Africa (ca. 700) and in the Middle East (ca. 700 formations). These will soon be joined by Japan (ca. 600 formations) and basins in South America (ca. 700 formations). A multi-database search system (age, region, lithology keywords, etc.) enables all returned entries be displayed by-age or in alphabetical order. The genera in the "fossil" field are auto-linked to their entries and images in the online Treatise of Invertebrate Paleontology. With a single click, a user can plot the original extent of the geologic formation (or an array of regional formations of a specified age) onto different plate reconstruction models with the polygon(s) filled with the appropriate lithologic facies pattern(s). Our team collaborated with the Macrostrat team at Univ. Wisconsin (Madison) to interlink with their extensive regional facies-time compilations for North America and the ocean basins to enable a near-global coverage. Following the lead of Macrostrat's ROCKD app, this project is in partnership with UNESCO's Commission for the Geologic Map of the World and other geological surveys to enable linking online geologic map units for direct access to the lexicon details on that geologic formation and its former paleogeographic setting. Essentially, goal is to create a view of the sediments and volcanics that were accumulating onto the Earth's surface at any time in the past.The main website (https://geolex.org) has links to the growing array of regional lexicons.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.055 | 0.019 |
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".