Scientometric evaluation of 100-year history of Poultry Science (1921–2020)
Bibliographic record
Abstract
To have a better contribution to the poultry production community, the Poultry Science Association founded journals including Poultry Science (PS) at 1921. Now, after 100 yr of publishing, PS ranks between the top 10 journals in the category of "agriculture, dairy, and animal science". One hundred years after publishing the first paper in PS, the poultry industry has been completely revolutionized. Hence, it will be interesting to establish scientometrics study of the PS development during the last century. Therefore, based on findings of the current study, among countries/authors' collaborations, future research fronts, and possibility of hot topics in the coming years may be predictable. Accordingly, a total of 22,451 articles were retrieved. For content analyses, according to the PS categorization for subject areas, 14 different subject areas were developed, including "behavior, breeding and quantitative genetics, education and extension, health and welfare, immunology, management and environment, metabolism and nutrition, microbiology and virology, modeling, molecular biology, physiology and anatomy, production, products, processing and marketing, and reproduction". Considering the 100-yr of PS, the most frequent subject area was "nutrition and metabolism" (14,109 articles), and "modeling" (1,114 articles) attracted less scholarly attention. However, considering the last decade (2011-2020), the most important subject area was "molecular biology" (1,420 of 2,466 articles; 57.58%), followed by "modeling" (544 of 1,144 articles; 48.88%). Moreover, the most frequent poultry species/strains were broilers (retrieved in 6,156 articles), followed by laying hens, turkeys, and quail. Considering collaboration of countries and researchers, it can be said that a total number of 108 countries contributed to PS, with the most prolific country being United States (with 9,421 articles; 43.16%), followed by China, Canada, the Netherlands, and Japan. Among the authors, Harms RH (287 articles), and Siegel PB (208) were the most prolific authors, and Siegel PB and Dunnington EA (71 articles) had more collaborations. To study keyword trends, including 3 time periods broilers was the central co-occurrent keyword, while the importance of chickens and turkeys declined during the time. Salmonella spp. was a constant representative of poultry microbiology during 100 yr. While "nutrition and metabolism" was the most important subject area, nutrition-related keywords (major items) were not concentrated and co-occurred with a variety of keywords from different subject areas. While "molecular biology" ranked first over the past decade, the importance of "nutrition and metabolism" should not be ignored. In fact, in recent years, molecular basis of the nutrition has been studied. In big-data era and due to developing the molecular biology technologies, it seems that using mathematical modeling and computational methodologies will increase and probably remains as one of the most attractive research areas for scientists at least in the upcoming future decades.
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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 | 0.027 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.164 | 0.183 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".