Wantzen K. M. and Araujo R. (eds, 2018): The Giant Freshwater Pearl Mussel (Margaritifera auricularia) HandbookVolume 2 – Technical Manual: Monitoring, artificial reproduction, rearing techniques, and suggestions for habitat conservationwith contributions by Karl M. Wantzen, Rafael Araujo, Joaquin Soler, Catherine Boisneau, Nina Richard, Philippe Jugé, Yann Guerez, Laure Morisseau, Michèle De Monte, Keiko Nakamura and Vincent PriéUniversity of Tours, France, CNRS UMR CITERES, LIFE+ project 13BIO/FR/001162 „Conservation of the Giant Freshwater Pearl Mussel (Margaritifera auricularia) in Europe“. Tours (France) 109 pp.
Bibliographic record
Abstract
The Giant Freshwater Pearl Mussel (Margaritifera auricularia) is one of the rarest invertebrate species worldwide. This two-volume book aims to bring together all the so far available information on the species. Both volumes are independent books, although they can be seen as complimentary, giving scientific and technical information. They result from work by the authors in the context of the LIFE+ project 13BIO/FR/001162 „Conservation of the Giant Freshwater Pearl Mussel (Margaritifera auricularia) in Europe“ and include additional work by the contributors from other conservation and research projects.Volume 2 is a manual that focuses on the practical aspects. It delivers hands-on information on how to find then animals in the field, how to identify them, how to study their habitats, how to prepare and run a laboratory for artificial reproduction and rearing, informs about release techniques, as well as descriptions of methods how to reinforce populations by infesting and releasing alternative host fish, or how to preserve mussel habitats. For a review of the literature on the species, please refer to Volume 1.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.051 |
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".