Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This Special Issue of Canadian Metallurgical Quarterly (CMQ) comprises selected papers from the 5th International Symposium on Aerospace Materials and Manufacturing: Advances in Materials, Processes and Repair Technologies, which was held last year in Vancouver as part of the 2010 Conference of Metallurgists (COM 2010). The symposium was a great success, drawing scientific and technical contributions from academia, industry and research laboratories worldwide. It was with great honour that we accepted the invitation from the Editor-In-Chief of CMQ, Dr. Doug Boyd, to develop a CMQ special issue as Guest Editors to highlight the quintessential themes from the symposium. The papers presented in this Special Issue cover a wide range of research and technology development topics in high temperature alloys, lightweight materials, manufacturing processes and modeling, protective coatings, and applications challenges. We wish to acknowledge the authors for their excellent contributions and the peer reviewers for their timely and insightful critique of the manuscripts that greatly improved the quality of the final versions. We also wish to extend our sincere appreciation to both Debbie Fisher of CMQ and Emma Leighton of Maney Publishing for their immeasurable support in producing this Special Issue.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.064 | 0.005 |
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 it