The top 101 cited articles in environmental clean-up: Oil spill remediation
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
<div> <p>The aim of this search was to identify the 101 top cited articles in the field of oil spill remediation. A search was conducted based on a database of the Web of Science included the journal citation reports from 1980 to 2013. The number of citations of the first 101 top cited articles is from 24 to 816. The decades with most top-cited articles published were 2000-2009 (47 articles) and 1990-1999 (37 articles). The most common research area of study was environmental science ecology. All the articles were published in 54 different journals in this category. Journals with the highest number of cited articles were <em>Applied and Environmental Microbiology</em> (10 articles), <em>Environmental Science and Technology</em> (6 articles), <em>Organic Geochemistry </em>(6 articles), <em>Chemosphere</em> (5 articles). Among the top cited articles the mostly named author were Sakkata Y, and Uddin MA with 6 of articles, followed by Fedorak PM with 5. Out of 101 top cited articles, 14, 13 and 12 articles originated from Canada, USA and France, respectively. Okayama and Alberta Universities were the most common productive institutions. Based on our knowledge, this is the first report of the 101 top cited articles in this category.</p> </div> <p>&nbsp;</p>
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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 it