Research in Petroleum and Environment: A Bibliometric Analysis in South America
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
Petroleum is a crucial resource that has globally influenced the scientific community and socio-economic development. However, its industrial processes negatively affect the natural environment. This research aims to analyse the intellectual structure of the petroleum and environment relationship in South American countries' contributions through bibliometric methods. The study presents a methodology: i) establishing search criteria; ii) initial search results; iii) refinement of results; iv) data analysis. Bibliometric methods were incorporated to analyse the performance of scientific production, and its mapping, allowing to reveal its structure. The results show a growth of this field of study (538 articles) through the contribution of countries, institutions and authors. Most of the studies related to oil and environment carried out by Brazil (399 articles) have a strong collaboration with Argentina, Colombia and Uruguay and partnerships with countries outside the region such as the United States, United Kingdom, and Spain. In addition, seven research themes were found (Biomarkers-petroleum derivatives, bioremediation, bioproductive processes, hydrocarbon-environmental, pollution effects, mangrove pollution, oil spill-simulation). This study provided relevant information on environmental pollution reflected in diverse sectors of South America (coastal and Amazonian areas). It showed several environmental remediation methods focused on microorganisms, biosurfactants, microbial residues, ionic processes and phytoremediation. Therefore, this research allows us to obtain meaningful and current information on the art state in this field of study.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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