A mineral deposit data base structure and a data base of VMS and Sedex deposits
Bibliographic record
Abstract
This database, VMSSEDEX in MS-Access[TM]-2.0 format, was created specifically for the compilation of geological, geochemical and economic data of volcanogenic massive sulphide (VMS) and sedimentary exhalative (Sedex) mineral deposits. The structure of the data base is versatile, and is easily adaptable to other deposit types. It consists of three tiers: DISTRICT SCALE: regional information which is applicable to all deposits in the district (e.g. geographical information; regional stratigraphy; geological province) DEPOSIT SCALE: information on a single geological deposit (e.g. grade and tonnage, geochemical and geophysical signatures; alteration; deposit scale zonation; local stratigraphy). LENS SCALE: information on geologically distinct parts of the deposit such as individual massive sulphide lenses and stockwork zones. The geological and geochemical data include those parameters compiled at the lens scale plus parameters such as physical dimensions. The data base consists of about eighty tables plus various pick-lists and data entry forms. Also included in the compressed file is a software module called VMS.MDB. Running of this module modifies some database forms to give extra menu bar buttons that enable the user to create extra tables that calculate aggregate grade and tonnage figures for production, economic reserves, sub-economic reserves and geological resource at the deposit scale and total economic resource and total geological resource at both the deposit and district scales. Also included in the compressed file is an ENDNOTE[TM]-2.0 database of references for each entry in the VMSSEDEX data base. These references have also been included as a table of text strings in VMSSEDEX to facilitate quick retrieval of the data source.
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.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.036 |
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".