Vadose Zone Journal 2018 Summary of Editorial Reports
Bibliographic record
Abstract
The year 2018 has been a landmark year for Vadose Zone Journal for several reasons.First of all, from 1 Jan. 2018, VZJ flipped from a subscription journal to a golden open access (OA) journal.This now makes the research published in VZJ accessible to a global readership, and it expands our visibility and impact beyond the vadose and critical zone research community.This flip went smoothly, and it was prepared and implemented in an excellent manner by our editorial office and the Tri-Societies.It could not have succeeded without the relentless support and engagement of Pamm Kasper, VZJ managing editor, and our publication system managers Lauren Coleman and Abby Morrison.We are also grateful for the support that we received from the board of the Tri-Societies and the Soil Science Society of America in making this change.Secondly, the international visibility and attractiveness of VZJ has continued to improve.The impact factor (IF) of VZJ for 2017 reached an all-time high of 2.7 since its beginning, and it increased by 0.7 compared with 2016.We are now again a Q1 journal in water research, and we are confident that we will become Q1 again in soil and environmental research in the next years.The reasons for the increased IF are several-fold, but key to this success is the high quality of papers that we have received in the last years, the establishment of update papers, as well as the publication of reviews that were very well received.Several review and update papers showed very high download rates for several months.On 15 Nov. 2018, VZJ had 11 highly cited papers, eight of which were published between 2016 and 2018.We welcome the new Editor of VZJ, Markus Flury, who will begin his term on 1 Feb. 2019.Markus is currently Professor of Soil Physics/Vadose Zone Hydrology at the
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 | 0.013 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.088 | 0.061 |
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".