The evaluation of the biorefinery research: A scientometric approach
Bibliographic record
Abstract
The present study explores the characteristics of the biorefinery literature published during the last three decades based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) and its implications using the scientometric techniques. The results of this study reveal that the biorefinery research output and the citations received have grown exponentially during the last decade after low performance of two decades triggered by the 2001 Twin-Tower terrorist attacks renewing the global anxiety on the energy supplies, with paralleling enormous changes in the research landscape. The US, Canada, and England have been the three most prolific countries. The "Michigan State Univ" of the US has been the most prolific institution and "Dale BE" of this university has been the most prolific author. "Bioresource Technology" has been the most prolific journal whilst "Biotechnology Applied Microbiology" has been the most prolific subject area. "H-index" has been 51 and a review paper on the biorefinery as a new manufacturing paradigm has had the highest impact on the literature with 994 citations. The scientometric analysis has a great potential to gain valuable insights into the evolution of the research on the biorefinery, complementing the scientometric studies in the other fields of the renewable energies as well as other dynamic research fields providing a unique insight on the incentive structures for all the key stakeholders in the field.
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How this classification was reachedexpand
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 | 0.070 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.056 | 0.578 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".