Molecular-Based Diversity Studies and Field Surveys Are Not Mutually Exclusive: On the Importance of Integrated Methodologies in Mycological Research
Bibliographic record
Abstract
Understanding and describing the diversity of living organisms is a great challenge. Fungi have for a long time been, and unfortunately still are, underestimated when it comes to taxonomic research. The foundations were laid by the first mycologists through field observations. These important fundamental works have been and remain vital reference works. Nevertheless, a non-negligible part of the studied funga escaped their attention. Thanks to modern developments in molecular techniques, the study of fungal diversity has been revolutionized in terms of tools and knowledge. Despite a number of disadvantages inherent to these techniques, traditional field-based inventory work has been increasingly superseded and neglected. This perspective aims to demonstrate the central importance of field-based research in fungal diversity studies, and encourages researchers not to be blinded by the sole use of molecular methods.
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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 | 0.040 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".