SCC 2014 Technical Program Committee
Bibliographic record
Abstract
Michel Occello, Pierre Mendes France University, France Jean-Paul Jamont, Universite de Grenoble, France Luis-Felipe Rodriguez, Instituto Tecnologico de Sonora, Mexico Yasmin A. Rios-Solis, Universidad Autonoma de Nuevo Leon, Mexico Osvaldo Cairo, Instituto Tecnologico Autonomo de Mexico, Mexico Marios D. Dikaiakos, University of Cyprus, Cyprus Mohand-Said Hacid, Universite Claude Bernard Lyon 1, France Sarūnas Girdzijauskas, KTH, Sweden Murat Kantarcioglu, University of Texas at Dallas, USA James Joshi, University of Pittsburg, USA Massimo Mecella, University of Rome, Italy Athman Bouguettaya, RMIT, Australia Bugra Gedik, Bilkent University, Turkey Shangguang Wang, Beijing University of Posts & Telecommunications, China Zaiwen Feng, Wuhan University, China Anand Dersingh, Assumption University, Thailand Lalita Narupiyakul, Mahidol University, Thailand Sherif G. Aly, The American University in Cairo, Egypt Sumon Shahriar, CSIRO, Australia Jungpil Shin, The University of Aizu, Japan Jinan Fiaidhi, Lakehead University, Canada Hoda M. Hosny, The American University in Cairo, Egypt Wesley Gifford, IBM T. J. Watson Research Center, USA Dashun Wang, IBM T. J. Watson Research Center, USA Nan Shao, IBM T. J. Watson Research Center, USA Sechan Oh, IBM Almaden Research Center, USA Guangjie Ren, IBM Almaden Research Center, USA Yu Deng, IBM T. J. Watson Research Center, USA E E Jan, IBM T. J. Watson Research Center, USA Sai Zeng, IBM T. J. Watson Research Center, USA Yixin Diao, IBM T. J. Watson Research Center, USA Remco Dijkman, Eindhoven University of Technology, The Netherlands Claude Godart, University Henri Poincare, France Akhilesh Bajaj, The University of Tulsa, USA Dickson Chiu, The University of Hong Kong, Hong Kong Hong-va Leong, Hong Kong Polytechnic University, Hong Kong Qing Li, City University of Hong Kong, Hong Kong Dragan Gasevic, Simon Fraser University, Canada Tilmann Rabl, University of Toronto, Canada Masahiro Tanaka, National Institute of Information and Communications Technology (NICT), Japan Ladjel Bellatreche, LIAS/ISAE-ENSMA, France Vijay Varadharajan, Macquarie University, Australia Armin Haller, CSIRO, Australia Luis Vaquero, HP Lab, UK Miguel Vargas Martin, University of Ontario Institute of Technology, Canada Fabio Casati, University of Trento, Italy Hangwei Qian, VMware, Inc., USA Junhua Ding, East Carolina University, USA Eleanna Kafeza, Athens University of Economics and Business, Greece Wei-Tek Tsai, Arizona State University, USA Jie Xu, University of Leeds, UK San-Yih Hwang, National Sun Yat-sen University, Taiwan Xiaoling Wang, Eash China Normal University, China
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.545 | 0.632 |
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".