Barcoding Fauna Bavarica – Capturing Central European Animal Diversity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Barcoding Fauna Bavarica (BFB) is an All Species \nBarcoding campaign ran by the Zoologische Staatssammlung in \nMunich and the Canadian Centre for DNA Barcoding (www. \nfaunabavarica.de). Core funding comes from the Bavarian Ministry \nfor Science, Research and the Arts and from Genome Canada \nthrough the Ontario Genomics Institute. The initial funding period is \nfrom 2009–2013. Bavaria has the highest biodiversity of all German \nstates, with at least 35000 animal species reported, representing a \nsignificant portion of the central European species diversity. \nEcoregions include high altitude biomes, foothill areas and forested \nlowlands. The Zoologische Staatssammlung (ZSM) is one of the \nlargest German natural history research institutions. It holds the \nworld’s largest collection of Lepidoptera and Germany’s largest \nHymenoptera collection. Since mid-2009, the BFB project has \ncontributed DNA barcode records from 7208 specimens representing \n3000 species and is therefore, after less than one year, one of the \nmost comprehensive sources for local DNA barcode data. The focus \ngroups for the initial phase were Lepidoptera (1820 species \nbarcoded), bees (316 species), ants (39 species) and aquatic insects \n(322 species). Work on these focal groups will continue during 2010, \nwith the goal to complete 80% of the Bavarian focal group species by \nthe end of the year. New focal groups are Diptera, Mollusca, all \nVertebrata and terrestrial Coleoptera, targeting 2000 species in 2010. \nMost tissue samples come from specimens in the ZSM collection, \nand where this was not feasible from freshly collected and identified \nspecimens. This rapid progress reflects the strong involvement of \ntaxonomists throughout the process, which is one of our key missions. \nWe have implemented a system which co-ordinates vouchers stored \nin our main collection, with tissues as well as DNA samples in our \nDNA bank.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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 it