Unveiling the nature of a miniature world: a horizon scan of fundamental questions in bryology
Bibliographic record
Abstract
Introduction Half a century since the creation of the International Association of Bryologists, we carried out a review to identify outstanding challenges and future perspectives in bryology. Specifically, we have identified 50 fundamental questions that are critical in advancing the discipline.Methods We have adapted a deep-rooted methodology of horizon scanning to identify key research foci. An initial pool of 258 questions was prepared by a multidisciplinary and international working group of 32 bryologists. A series of online surveys completed by a broader community of researchers in bryology, followed by quality-control steps implemented by the working group, were used to create a list of top-priority questions. This final list was restricted to 50 questions with a broad conceptual scope and answerable through realistic research approaches.Key results The top list of 50 fundamental questions was organised into four general topics: Bryophyte Biodiversity and Biogeography; Bryophyte Ecology, Physiology and Reproductive Biology; Bryophyte Conservation and Management; and Bryophyte Evolution and Systematics. These topics included 9, 19, 14 and 8 questions, respectively.Conclusions Although many of the research challenges identified are not newly conceived, our horizon-scanning exercise has established a significant foundation for future bryological research. We suggest analytical and conceptual strategies and novel developments for potential use in advancing the research agenda for bryology.
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 | 0.020 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.017 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".