Proceedings of the Congress on Numerical Methods in Engineering CMN 2022
Bibliographic record
Abstract
This book contains the Proceedings of the “Congress on Numerical Methods in Engineering (CMN 2022)” (https://congress.cimne.com/cmn2022), which took place from 12th to 14th September 2022 in Las Palmas de Gran Canaria, Spain, organized by the “Sociedad Española de Mecánica e Ingeniería Computacionales” (SEMNI, Spain) and the “Associação Portuguesa de Mecânica Teórica, Aplicada e Computacional” (APMTAC, Portugal); and hosted by the local organization of the Institute of Intelligent Systems and Numerical Applications in Engineering (SIANI), and the collaboration of their Department of Mathematics, Department of Civil Engineering, and the School of Industrial and Civil Engineering of the University of Las Palmas de Gran Canaria (ULPGC), totalling more than 150 contributions accepted after scientific peer review (coming from Spain, Portugal, Italy, Poland, Belgium, France, Luxemburg, Switzerland, Germany, United Kingdom, México, Chile, United States, Canada and Australia), whose abstracts or full papers constitute this volume.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".