Bibliographic record
Abstract
8 IC0T0M19 (2021) It is our great pleasure to welcome all of you to the 19th International Conference on Textures of Materials (ICOTOM-19), which is held in Japan from March 1 to 4, 2021. First and foremost, we would like to thank all of participants for understanding that the conference was postponed by six months and held virtually, in consideration of COVID-19 pandemic. ICOTOM19 should have been held at Osaka Prefecture University (OPU), Sakai, Japan from September 6-11,2020. The organizing committee decided in April, 2020 to postpone holding the conference by six months, as better situation would be expected. Further, the committee selected a virtual format as the most appropriate plan when holding actual conference at OPU became unrealistic in consideration of the current situation regarding the COVID-19 pandemic. The first Virtual conference belongs to the series of ICOTOM meetings with a history of 52 years. The conference started in Clausthal in 1969 and it has been held about every 3 years as follows: Cracow-1971, Pont-à-Mousson-1973, Cambridge-1975, Aachen-1978, Tokyo-1981, Noordwijkerhout-1984, Santa Fe-1987, Avignon-1990, Clausthal-1993, Xian-1996, Montreal-1999, Seoul-2002, Leuven-2005, Pittsburgh-2008, Mumbai-2011, Dresden-2014 and St. George-2017. It is indeed our great honor to hold an ICOTOM conference in Japan or organized by Japanese colleagues again after 40 years. Following the tradition of ICOTOM conferences, ICOTOM-19 focuses on the fundamental understanding of the basic processes underlying the formation of texture and its relation to the properties. ICOTOM-19 thus provides a forum for the presentation and discussion on recent progress in crystallographic texture and related mechanical and functional properties of all kinds of polycrystalline materials. We invite all the scientists and engineers from many different areas working under the common theme of crystallographic orientation and texture to exchange ideas with the aim of linking basic research with an application. The proceedings contain 49 papers, including the precious Plenary Lectures by Prof. Rollett and Prof. Kestens, with a significant knowledge in the research field on the crystallographic orientation, texture and related properties. We hope that these papers will be attractive and useful for all researchers in this field. We would like to thank the many colleagues who helped in organizing the conference and especially Virtual Conference Team members, Prof. Makoto Hasegawa, Dr. Yusuke Onuki, Dr. Natsuko Sugiura, Dr. Shigehiro Takajo, Dr. Yasuaki Tanaka and Prof. Hiroshi Utsunomiya. Prof. Masakazu Kobayashi, Mr. Toshiaki Takasaki, G.T. Center and reviewers also made substantial contributions to the editing of the proceedings. We should also thank Prof. Yasuyuki Kaneno, Prof. Shigeo Sato and Mr. Seiichi Suzuki for their devoted contributions to the realistic conference preparation. Finally, we would like to express our thanks to The Light Metal Educational Foundation, Inc., The Amada Foundation, The Iron and Steel Institute of Japan, The Japan Institute of Metals and Materials for their financial supports and many companies and organizations for their encouragements. List of ICOTOM19 committees, Local organizing committee, Local advisory committee, are available in the pdf
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.610 | 0.458 |
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".