New core and downhole geophysical data sets from the Bells Corners Borehole Calibration Facility Ottawa, Ontario
Bibliographic record
Abstract
The Geological Survey of Canada's deep borehole test site at the Bells Corners Borehole Calibration Facility in Ottawa, Ontario, has been in use since the 1980's for the development and calibration of geophysical logging instrumentation. Cores from six deep boreholes (up to 300 m) are preserved and remain available for research purposes. In 2019, the facility underwent repairs to reopen deep boreholes, replace surface casings, and install atmospheric monitoring equipment. This report documents new laboratory core testing and downhole geophysical logs collected in borehole BC81-2, the most frequently logged of the boreholes at the facility. Core data sets include physical, mechanical, and hydraulic properties, nuclear magnetic resonance, and complex resistivity measurements. The downhole log suite includes televiewer imagery (optical and acoustic), total gamma, full waveform sonic, and fluid measurements (high resolution temperature, conductivity, and flow meter measurements). Digital data are provided in appendices. These data sets support ongoing collaborations at the Facility across a variety of disciplines for geological exploration, geoengineering, and hydrogeological research.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".