A new approach to an old conundrum—DNA barcoding sheds new light on phenotypic plasticity and morphological stasis in microsnails (Gastropoda, Pulmonata, Carychiidae)
Bibliographic record
Abstract
The identification of microsnail taxa based on morphological characters is often a time-consuming and inconclusive process. Aspects such as morphological stasis and phenotypic plasticity further complicate their taxonomic designation. In this study, we demonstrate that the application of DNA barcoding can alleviate these problems within the Carychiidae (Gastropoda, Pulmonata). These microsnails are a taxon of the pulmonate lineage and most likely migrated onto land independently of the Stylommatophora clade. Their taxonomical classification is currently based on conchological and anatomical characters only. Despite much confusion about historic species assignments, the Carychiidae can be unambiguously subdivided into two taxa: (i) Zospeum species, which are restricted to karst caves, and (ii) Carychium species, which occur in a broad range of environmental conditions. The implementation of discrete molecular data (COI marker) enabled us to correctly designate 90% of the carychiid microsnails. The remaining cases were probably cryptic Zospeum and Carychium taxa and incipient species, which require further investigation into their species status. Because conventional reliance upon mostly continuous (i.e. nondiscrete) conchological characters is subject to fallibility for many gastropod species assignments, we highly recommend the use of DNA barcoding as a taxonomic, cutting-edge method for delimiting microsnail taxa.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".