Long and Short-Term Impact of Papers in <i>Applied Spectroscopy</i>
Bibliographic record
Abstract
In 1955, Eugene Garfield introduced the concept of a journal impact factor as a metric for measuring the importance or influence of scholarly journals. These days a journal's fate is often tied strongly to the impact factor. It is a topic that comes up regularly and a source of concern for the journal because of the slavish focus on metrics in the publishing world and in the academic community. From our perspective, the impact factor is shown to be a poor metric for illustrating the long-term significance of papers published in Applied Spectroscopy. The five-year impact factor is a better indicator for the short-term impact of the papers published in this journal, while the cited half-life and the citing half-life both provide a better measure of the long-term impact of papers published in Applied Spectroscopy. Of the most highly cited papers published in this journal, those that describe innovative data processing techniques have been cited more than papers that describe specific applications of a given technique such as infrared (IR), Raman, or laser-induced breakdown spectroscopy (LIBS).
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one teacher head, 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".