Mini Reviews: A new manuscript category for summarizing emerging topics
Bibliographic record
Abstract
Molecular Ecology (MEC) publishes cutting-edge research that utilizes molecular genetic techniques to address consequential questions in ecology, evolution, behaviour and conservation. Molecular Ecology Resources (MER), our companion journal, publishes methodological papers including analytical methods and genome resources that facilitate research within this field. In addition, both journals publish Invited Reviews (MEC) or Invited Technical Reviews (MER). Review articles provide valuable ‘one stop’ overviews of complex topics, and can also introduce new perspectives that emerge from broad analyses. Mini Reviews will not normally exceed 3000 words with a maximum of two figures or tables, although authors can request modifications to these guidelines if appropriate. A Mini Review should provide a brief background, a summary of the research conducted so far, and recommendations for future investigations and applications that will increase our understanding or utilization of the topic. We will consider unsolicited Mini Reviews, although we encourage interested authors to contact the Editorial Office prior to submission: [email protected]. Owing to the novelty and relative brevity of Mini Reviews, we will aim for short turn-around times in assessing and reviewing these papers. We look forward to receiving cutting-edge insightful Mini Reviews that will be of great interest to readers of MEC and MER.
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 | 0.027 | 0.131 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.102 | 0.113 |
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".