Does ecological interface design scale up to industrial plants?
Bibliographic record
Abstract
The purpose of this research was to determine how the principles of ecological interface design (EID) could be applied to systems that are larger in scale than those that had been previously used as testbeds for evaluating EID. The focus of this initial feasibility study was the feedwater subsystem of Asea Brown Boveri's (ABB's) conventional power plant simulator. The primary outcome of this research is a prototype interface for the feedwater subsystem that is based on the EID framework. The main findings of this study are: a) a proof of concept showing that the principles of EID can be meaningfully applied to a larger-scale design problem representative of those found in industry; b) EID needs to be supplemented by more specific interface design principles; and c) it is possible to effectively integrate EID with these other design principles. Therefore, EID seems to be a viable candidate for the design of advanced computer interfaces for complex industrial plants.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.035 | 0.011 |
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; both teacher heads agree on what is shown here.
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".