A PEER REVIEWED ONLINE COMPUTATIONAL MODELING FRAMEWORK
Bibliographic record
Abstract
Along with theory and experimentation, computational simulation has become the third pillar of scientific discovery. While in industry computational modeling has seen application at an enterprise-wide level in the context of Model-Based Design, in academia models are typically still limited to isolated use by specialists. Once a project is completed, the intellectual property embodied by the model is lost. To harness the effort spent, a networked repository is proposed that stores peer-reviewed models. These models are evaluated whether they adhere to a set of quality requirements so they capture intrinsic value. This would facilitate the type of multi-disciplinary collaboration that is required to engineer the systems that have emerged and that continue to gain in importance. This work puts forward an outline of such a peer-reviewed online repository.
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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 | 0.027 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.013 | 0.009 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.027 |
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".