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Record W6968735074 · doi:10.5281/zenodo.3867388

Leptoiulus montivagus

2017· article· en· W6968735074 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsEndangered speciesHabitatPopulationMossMillipedeGrassland

Abstract

fetched live from OpenAlex

332. Leptoiulus montivagus (Latzel, 1884) Iulus montivagus Latzel, 1884. Iulus braueri Verhoeff, 1895. Iulus tosanus Verhoeff, 1916. Leptoiulus braueri auct. Leptoiulus weberi Verhoeff, 1927. Leptoiulus tosanus zurstrasseni Verhoeff, 1929. Leptoiulus catascaphicus Verhoeff, 1931. Leptoiulus triglavensis Strasser, 1940. Distribution AT, CH, CZ, DE, FR-FRA, IT-ITA, SI. Alpine. Habitat Alpine meadows, under stones. In Switzerland it is found in pastures and dry grassland from as low as 280 m in the north. In the south it occurs from 920 to 2860 m (Pedroli-Christen 1993). It reaches 2400 m in Slovenia, where it was found under stones and in cushions of turf (Strasser 1940). In Bavarian woods it may be found under decaying bark and below moss on blocks of granite (Schubart 1934). Kobel- Lamparski (1987) found it to be the most abundant millipede in vineyards in Kaiserstuhl, southern Germany, and gave detailed information on its population structure. Remarks Among all the species of Leptoiulus with complicated taxonomic histories, L. montivagus probably takes the prize. It seems to be a relict species surviving at high altitudes, formerly widespread during the ice age, and since then the now isolated populations on the summits of mountain chains have diversified to some degree. Regarded as highly endangered in Germany (Voigtländer et al. 2011).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.005

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.

Opus teacher head0.037
GPT teacher head0.231
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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