Preview: Geomechanics and Tunnelling 4/2015
Bibliographic record
Abstract
Abstract Best of EUROCK 2015 & 64. Geomechanics Colloquium / Ausgewählte Beiträge des Symposiums EUROCK 2015 & des 64. Geomechanik Kolloquiums J.J. Day, M.S. Diederichs, D.J. Hutchinson: Effects of structural contact stiffness and strength on progressive failure of healed structure N. Isago, K. Kawata, A. Kusaka, T. Ishimura: Long‐term deformation of mountain tunnel lining and ground under swelling rock condition S. Pausz, H. Nowotny, G. Jung: Rock mass classification and geotechnical model for the foundation of a RCC gravity dam C.L. Zhang: Long‐term deformation of clay rock under various thermo‐hydro‐mechanical conditions G. Walton, M.S. Diederichs, A. Punkkinen: Influence of Constitutive Model Choice on Simulated Stress Path and Yield Evolution in Deep Mine Pillar Analysis – Experience from the Creighton Mine, Sudbury, Canada P. Bagga, D.G. Roy, T.N. Singh: Effect of carbon dioxide sequestration on the mechanical properties of Indian coal G. Barla, D. Debernardi, A. Perino: Lessons learned on deep‐seated landslides activated by tunnel excavation S. Giger, P. Marschall, B. Lanyon, C.D. Martin: Hydromechanical response of Opalinus Clay during excavation works – a synopsis from the Mont Terri URL T. Marcher, S. Bauer, M. Allende, C. Mathiesen: Valhalla – innovative pumped hydro storage facilities in Chile – challenges from a rock mechanical point of view W. Schubert, B. Moritz: State of the art in monitoring and geotechnical safety management for shallow and deep tunnels T. Camus, F. Therville: Sydney North West Rail Link project – 4 double shield TBMs excavate 15 km of twin tunnels
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.699 | 0.476 |
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".