Bibliographic record
Abstract
Based on the Web of Science database and using biblionmetric method,this paper analyzed the trend of published cherry literature in the world from 2000 to 2013,and also reviewed the research institutes,core authors,key journals,subject categories and research hot spots of the countries with published paper quantity ranking at world top 5.The result indicated that there were 1 794 cherry research papers all over the world.The paper production as a whole showed a rising trend,with the top quantity in 2012,which was almost 2.288 times of that in 2005.The top 5countries were the United States,Turkey,Spain,Germany and Italy.The United States published 376 papers,taking the first place.Except Germany,the other 4 coutries were among the world top 5 in cherry production,illustrating that their strong scientific research ability did promote the development of cherry industry.The world top 5 institutions with high cherry academic paper quantity were USDA-ARS,Michigan State Unversity,Washington State University,Agriculture Agri-Food Canada,and University of Extremadura in Spain.The core authors with high academic achievement were mainly from the United States. Scientia Horticulturae, Hortscience, Journal of Agricultural and Chemistry, Postharvest Biology and Technology and Food Chemistry were the major journals in this field.The main disciplines of these published cherry literature were agriculture,food science technology,plant science,chemistry and environmental science ecology.The research hot spots were focused on fruit quality,disease,anthocyanin,rootstock and post harvest mechanism.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.124 | 0.162 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".