The IGCP 509 database system: design and application of a tool to capture and illustrate litho- and chrono-stratigraphic information for Palaeoproterozoic tectonic domains, large igneous provinces and ore deposits; with examples from southern Africa
Bibliographic record
Abstract
Abstract The IGCP 509 project is collating global information for the Palaeoproterozoic era through the activities of numerous international collaborators. A database system (StratDB) and web interface has been designed to facilitate this process with links to an existing geochronology database (DateView). As a result, all information captured will remain available in a digital format for future researchers. The philosophy and design of the database and some of the outputs available from it are described. One of the principal features of the system is that it facilitates the construction of time–space correlation charts using an innovative application of GIS technology to non-geographic information, which permits users to query a variety of attribute information associated with lithostratigraphic units, metamorphic and deformation episodes associated with user-selected tectonic domains, large igneous provinces and major ore deposits. In the process, much of the manual labour normally associated with the construction of such charts in standard graphical or drafting packages is avoided. Associations between units, deformation, metamorphism, large igneous provinces and ore deposits may become more apparent once linked information is available for querying and investigation. Geochronological information from the DateView database may also be linked to entities stored in StratDB. GIS maps may be linked to the attribute information in StratDB and DateView to construct a variety of time-slice maps or palaeogeographic reconstructions with the same symbology as is used in the time–space correlation charts. This database system will facilitate the dissemination of lithostratigraphic information for many countries to a broader community and will help non-specialists to easily view information for various Palaeoproterozoic tectonic domains. The system is illustrated using a preliminary compilation of information for the Palaeoproterozoic of southern Africa. The correlation charts and time-slice maps provide insights to the geological evolution of this region which emphasize some aspects and correlations which have not previously been extensively considered; for instance, possible correlation of units in the central and western zones of the Limpopo Belt (South Africa, Zimbabwe and Botswana) with the Magondi Belt of Zimbabwe and its extension into northern Botswana.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| 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".