Origin, evolution, currents of thought, and methodological implications of the agroecosystem concept: a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT. The objective of the research was to analyze the different currents of thought and to describe the origin and evolution of the concept of agroecosystems across different studies. Methodology. A state-of-the-art analysis of the agroecosystem concept was conducted using the Web of Science platform, considering 225 articles with the TITLE "Agroecosystem" AND KEYWORDS "Agroecosystem." Metrics such as year, country, sustainable development goals (SDGs), language, summary, and conclusions were also considered. A bibliometric analysis was performed using VOSviewer software, and graphs were created to visualize the bibliographic connections between the documents obtained from the Web of Science database. Results. Articles from 1991 to 2024 were identified, with over 90% published from 2018 to the present. The top countries publishing this type of research are the USA, China, Canada, France, Germany, and Italy, accounting for 82% of the publications. The remaining 18% are spread across 44 countries worldwide. The predominant language is English (96%), followed by Spanish (3.1%) and Russian (1%). Conclusions. The concept of agroecosystems is embedded in the social, cultural, political, and economic contexts, as all these aspects are directly related to agriculture, livestock, fishing, and other essential activities for feeding humanity. These activities are carried out within agroecosystems managed by humans for both commercial and self-consumption purposes, aiming to satisfy society's demand for food, goods, services, and inputs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it