Generic transformation models for some intact rock properties
Bibliographic record
Abstract
A global intact rock database of nine parameters, including uniaxial compressive strength and Young’s modulus, is compiled from 184 studies. This database, labeled as “ROCK/9/4069”, consists of 27.5% igneous rock, 59.4% sedimentary rock, and 13.1% metamorphic rock. The vast majority (>95%) of intact rocks in the database are in their natural moisture contents. About 14% of the data points are for weathered rocks and about 4% are foliated metamorphic rock. It is found that most existing transformation models are data-specific or site-specific in the sense that they fit well to their own calibration databases, but do not necessarily fit well to ROCK/9/4069. One can infer that transformation models for intact rocks are more data–site dependent than those for soils. It is evident that ROCK/9/4069 has coverage wider than most existing transformation models. The ROCK/9/4069 database is then adopted to calibrate the bias and variability of existing transformation models. Transformation models with relatively large application ranges and relatively small transformation uncertainties are selected as generic transformation models. These generic models can be valuable for scenarios where site-specific models are not available, e.g., construction projects with insufficient budget or the preliminary design stage of a project.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".