View‐based process elicitation: a user's perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Software process models are considered important for a number of purposes, such as assessment, improvement and customization. In order to obtain a complete model of a process, it is often necessary to gather relevant information from different sources (agents, documents, observations, etc.). One problem with this is that different sources may give inconsistent information about the same process. Resolving such conflicts can be difficult and arduous. This paper describes a user's perspective of a prototype tool, called V‐elicit, which helps in eliciting process models based on information from multiple sources. In V‐elicit, the information gathered from each source is entered separately as ‘views’, each of which is checked for internal consistency. Following this, common elements across the views are identified, and inconsistencies amongst them are flagged. As the elicitor, aided by the system, resolves these conflicts, the final (merged) model is automatically built. These features are illustrated through an example elicitation of a requirements engineering process. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it