Reviewer Acknowledgements for Journal of Plant Studies, Vol. 6, No. 2
Bibliographic record
Abstract
Journal of Plant Studies wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated.Journal of Plant Studies is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please find the application form and details at http://www.ccsenet.org/reviewer and e-mail the completed application form to jps@ccsenet.org.Reviewers for Volume 6, Number 2Ahmed Ghannam, University of Strasbourg, FranceAlfredo Benavente, Consejería de Agricultura, Pesca y Medioambiente, SpainAmi Lokhandwala, University of Mississippi, Department of Biology, USABingcheng Xu, Chinese Academy of Sciences and Ministry of Water Resources, ChinaChrystian Iezid Maia e Almeida Feres, Tocantins Federal University, BrazilEstelle Dumont, université Aix-Marseille, FranceHoma Mahmoodzadeh, Department of Biology, Mashhad Branch, Islamic Azad University, Mashhad, IranKhyati Hitesh Shah, Stanford University, United StatesKinga Kostrakiewicz-Gieralt, Institute of Botany, Jagiellonian University, PolandKonstantinos Vlachonasios , Aristotle University of Thessaloniki, School of Biology, GreeceMartina Pollastrini, University of Florence, ItalyMassimo Zacchini, National Research Council of Italy (CNR), ItalyMelekber Sulusoglu, Arslanbey Vocational School Kocaeli University, TurkeyMohamed Trigui, Sfax Preparatory Engineering Institute and CBS, TunisiaRajiv Ranjan, T. P. Varma College, IndiaRajnish Sharma, Dr YS Parmar University of Horticulture & Forestry, Solan (HP), IndiaRakesh Ponnala, Zoetis Inc, United StatesRocío Deanna, Instituto Multidisciplinario de Biología Vegetal, ArgentinaSaid Laarabi, University Mohammed V/Ministry of National Education, MoroccoSlawomir Borek, Adam Mickiewicz University, PolandSuheb Mohammed, University of Virginia, United StatesTomoo misawa, Donan Agricultural Experiment Station, Hokkaido Research Organization, Japan
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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 | 0.046 | 0.369 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.119 | 0.069 |
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".