SHORT COMMUNICATION ANALYSIS OF GEOMORPHOLOGY CITATIONS IN THE LAST QUARTER OF THE 20TH CENTURY
Bibliographic record
Abstract
Three hundred and twenty-eight geomorphology articles published in the last quarter of the 20th century were cited 20 or more times in Institute for Scientific Information (ISI) indices, as of 15 May 2001. At the close of the 20th century, wellcited geomorphology is highly multidisciplinary and interdisciplinary with the most dominant fields being in biological, civil engineering, earth science, geography, geological, and soils disciplines. The very strong English-language bias of well-cited journal articles creates a geographical bias in study site selection, which may in turn bias geomorphic theory. Water-based research (fluvial processes and landforms, riparian, drainage basin) dominates well-cited papers, with the ‘hottest ’ subfield in the 1990s being riparian research with a biological emphasis. Over 90 journals publish well-cited papers, but Earth Surface Processes and Landforms hosts the largest number of well-cited papers. Copyright © 2002 John Wiley & Sons, Ltd. KEY WORDS: geomorphology; landform; earth surface processes; citation; bibliometric; temporal; time; trends Garfield first proposed a citation index for analysing scientific literature (Garfield, 1955), leading to the creation of the Institute for Scientific Information (ISI). Bibliometric analyses, filtered through the ISI database,
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.
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 | 0.002 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.046 | 0.084 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".