Definition Please – A Rock Engineering Dictionary
Bibliographic record
Abstract
ABSTRACT: definition /def-i-ni-tion/ noun a statement of the meaning of a word, commonly found in a dictionary. Every discipline has its own language – domain specific terminology that allows practitioners to better understand the problem and communicate with one another. While some words and phrases are only found in one specific discipline, there are others that are found in a variety of related disciplines and subdisciplines. Examples in disciplines related and/or adjacent to rock engineering include the terms validation (which has differing definitions in machine learning compared to numerical modelling) and fines (which has differing definitions in soil mechanics compared to cave mining). Confusion may arise when these terms with differing discipline definitions are not defined in their specific context in the literature. Adding to this confusion is the misuse of certain terms in rock engineering, such as accuracy, precision, and quantifying. The goal of this paper is to clarify the definitions of rock engineering terms that are found in other related disciplines, as well as clarify the definitions of rock engineering specific terms. By providing this dictionary of rock engineering terms, we hope to standardize rock engineering vocabulary, allowing for clearer communication among practitioners and students. 1. INTRODUCTION For any rock engineers who competed in spelling bees in their childhood, the phrase "definition please" may ring a bell. During spelling bees, contestants are able to ask for the definition of a word ("definition please?") to help them spell it. While spelling bees are no longer an aspect of our lives after elementary school, asking for the definition of a word remains an important aspect of research and professional development. Every discipline has its own language – domain specific terminology that allows practitioners to understand the problem in greater detail and to better communicate with one another. Rock engineering language consists of its own terminology (such as rock mass rating or geological strength index) and terminology overlapping with other disciplines, such as with soil mechanics, statistics, and numerical modelling. Confusion may arise when terms are not defined in their specific context, especially those overlapping with other disciplines. This confusion is further exacerbated by the tendency of rock engineers to both misuse certain terminology (such as accuracy, precision, and quantity) and use others interchangeably when they do not have the same definition (such as imbalanced data/skewed data and calibration/validation). As a result, there is a clear need to clarify the definitions of certain rock engineering terms.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.062 | 0.046 |
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".