Advances in Mechanics of Solids
Bibliographic record
Abstract
Vibrations and Stability of Thin Structures: Eliza Haseganu's Analysis of Wrinkling in Pressurized Membranes (D J Steigmann) Buckling, Vibrations and Optimal Design of Ring-Stiffened Thin Cylindrical Shells (S B Filippov) Asymptotic Analysis of Thin Shell Buckling (A L Smirnov) Thin-Wall Structures Made of Materials with Variable Elastic Moduli (A L Smirnov & P E Tovstik) Asymptotic Integration of Free Vibration Equations of Cylindrical Shells by Symbolic Computation (E M Haseganu et al.) Vibrations and Stability in Continuum Mechanics: The Mechanics of Pre-Stressed and Pre-Polarized Piezoelectric Crystals (E Baesu) On the Stability of Transient Viscous Flow in an Annulus (A A Kolyshkin et al.) Biomechanics: Mechanical Models of the Development of Glaucoma (S M Bauer) A Micromechanical Model for Predicting Microcracking Induced Material Degradation in Human Cortical Bone Tissue (O Akkus et al.) Experimental and Computational Mechanics of Solids: An Evolution of Solid Elements for Thermal-Mechanical Finite Element Analysis (J Moyra & J McDill) Quantization Effects in Shallow Powder Bed Vibrations (J Pegna & J Zhu).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".