Bibliographic record
Abstract
The Editorial Office and Wiley-VCH would like to take the opportunity at this early stage of 2016, to thank all the authors, readers, referees and Editorial Board members for their continued support of Fuel Cells – From Fundamentals to Systems. Regarding the journal statistics, we currently have a rejection rate of 52% for 2014 and so far 49% for the submission year 2015 (21% are still under review), with almost the same number of manuscripts submitted. The raise of the rejection rate by 10% on submitted manuscripts is a testimony to the quality of the papers Fuel Cells – From Fundamentals to Systems publishes, which would not be feasible without our hard-working reviewers, who evaluate the submitted manuscripts. The increase of the Impact Factor by 30% and a 5-year average of 2.63 reveals our improved standards. As Fuel Cells – From Fundamentals to Systems is published fully online since 2011, some of the covered up-to-date topics in energy conversion and storage and the integration of related fields, i.e. microbial or enzymatic fuel cells (MFC/EFC) and electrolyzer, were mirrored by the steadily increasing usage of the journal's online version. To date, seven papers published in this year, are already under the top 10 most accessed papers in 2015. Of particular interest was the Original Research Paper on “The Case for Natural Gas Fueled Solid Oxide Fuel Cell Power Systems for Distributed Generation” by L. Chick et al. (Fuel Cells, 2015, 15, 49–60), which has been highly featured in the media. Therefore, we would like to mention to our readers and future authors again, that after a paper is published in the so-called “Early View”, it is fully citable using its digital object identifier (DOI). In 2016 we will further focus on improving the aimed high quality of publication in our journal, promoting top science and creativity. In 2016, we again plan to publish 2 Special Issues related to Conferences, which are consecutive for several years in Fuel Cells – From Fundamental to Systems. One will be “Bringing Hydrogen Fuel Cells & Hydrogen, as Part of Our Energy Future Closer to Deployment (EFCF2015)”, with F. Barbir, G. Radica and I. Tolj (University of Split, Croatia) as Guest Editors. In addition, we plan the Special Issue “Fundamentals & Developments of Fuel Cells Conference 2015 (FDFC2015)” with C. Turpin (University of Toulouse, France), Y. Bultel (University of Grenoble, France), D. Hissel and N. Yousfi-Steiner (both from Laboratory FEMTO-ST/FCLAB, Belfort, France) as Guest Editors in the second half of the year. Additionally, we have scheduled a Topical Issue on “Theory and Modeling of Fuel Cells” with M. Eikerling (Simon Frazer University Burnaby, Canada) in charge as Guest Editor, who will ensure that this issue will consist of high profile invited papers (Reviews and Original Research Papers). As another highlight we will implement a so-called “Virtual Issue”, which will be available online only and highlights already published papers in Fuel Cells – From Fundamentals to Systems, related to hot topics in this field of research. The new member of the Editorial Board, E. Hao Yu, took the opportunity to make herself known to our readers beeing the Guest Editor for the first Virtual Issue focusing on “Microbial and Enzymatic Fuel Cells”, which will appear early this year. Make sure to stay informed by subscribing to the ToC (Table of Contents) alert for Fuel Cells – From Fundamentals to Systems. We hope that the planned Topical and Virtual Issues will also have impact on future submissions on this topic. In this context we would encourage you to submit review articles but also original research papers on electrochemical energy technology in general. If you have a suggestion for a review article, please send it to the Editorial Office with a 1–3 page outline for a first evaluation. What is new on the Editorial Board? The Editorial Office and Wiley-VCH are pleased to officially welcome our new Editorial Board member, Eileen Hao Yu from Newcastle University. At the same time we like to say a special “Thank You!” to Jürgen Garche, whose term as an Editorial Board Member terminated with the end of 2015, for his years of continuous referee work, support and helpful advice. We are looking forward to receiving your best research paper as well as suggestions for potential review papers in the near future.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.111 | 0.086 |
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".