Improving the 3-D geological data infrastructure of southern Ontario: data capture, compilation, enhancement and QA/QC
Bibliographic record
Abstract
Well records of the Oil Gas and Salt Resources Library (OGSRL) are maintained in the Ontario Petroleum Data System (OPDS) and are the principal source of data on the subsurface geology of southern Ontario. In this project significant improvements have been made to data quality in OPDS through a process of capture and compilation of existing data, QA/QC edits to the existing data, and creation and addition of new data. Edits were completed to 30,320 formation top picks in 7,812 wells. These improvements were completed as part of the development of a 3-D lithostratigraphic model of the Paleozoic bedrock of southern Ontario. The completion of this QA/QC at the OGSRL has the permanent benefit that any future users of the library data will have access to these corrections. OPDS data supports resource industries involved in exploration for and development of salt, oil, natural gas, groundwater, compressed air energy storage, disposal of oil field fluids, geological storage of hydrocarbons, and permanent geological storage of nuclear wastes. It also supports public education and the training of new geoscientists and geological engineers. The southern Ontario 3-D model is data-driven. OPDS is the key source of data for the model and illustrates the value of a properly constructed and actively maintained wells database. Without OPDS the 3-D modelling project would not have been possible.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".