A Framework for Mineral Geoscience Data and Model Portability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We have developed a data structure called GEOH5 with the objective of integration and storage of geological models, data, and metadata where dissemination, ease of access, and persistence are required without commercial encumbrance. Our emphasis is on the needs of the mineral industry which, unlike the upstream oil and gas industry, otherwise lacks common data exchange formats with a scope encompassing most exploration and production data types. Although only a few years old, the data structure is already in use by many thousands of users with increasing acceptance across mineral geoscience and engineering. This includes industry, academia, and geological surveys that use GEOH5 as a documented, public, easy-to-use, vendor-neutral, and permanently accessible means of storage and communication. GEOH5 is open source and free to use. It is based on open-source HDF5 technology because of its many advantages: wide acceptance across numerous data-intensive industries, self-describing behaviour through integration of data and metadata, fast I/O, excellent compression, file merging, cross-platform capability, unlimited data size, and access to libraries in a variety of programming languages. It provides professionals, researchers, and the public at large with a robust means of managing, exchanging, and visualising large quantities of diverse mineral geoscience and engineering data.
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.
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 | 0.000 |
| 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 it