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Record W6893534967 · doi:10.5281/zenodo.3867226

Cylindroiulus truncorum

2017· article· en· W6893534967 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsWoodlandNearctic ecozoneConfusionHabitatPeriod (music)

Abstract

fetched live from OpenAlex

191. Cylindroiulus truncorum (Silvestri, 1896) Diploiulus truncorum Silvestri, 1896. Cylindroiulus luscus salicis Verhoeff, 1926. Distribution AT, BE, CH, DE, DK-DEN, ES-CNY, FI, FR-FRA, GB-GRB, GB-CI, GB-NI, HU, LU, NL, NO-NOR, PL, PT-MDR, PT-POR, SE, UA. Extended Atlantic. – Also North Africa (Algeria, Tunisia), introduced into Siberia and the Australian, Neotropical and Nearctic regions. Habitat Strongly synanthropic over most of its known range, found in botanical and other gardens, parks, cemeteries, horticultural nurseries, greenhouses, farms, in hay, on spoil heaps, quarries, scrub, in refuse on waste ground. There was an infestation of house walls in Belgium (Kime, 2004). Haacker (1968) found that it spread into surrounding woodland in West Germany, that it preferred high humidity and ate mainly leaves. Found in woodland litter in Portugal as well as Germany. In laurisilva with tree heather at 800–900 m on Tenerife (Monte de las Mercedes). Remarks Schubart (1934) thought that the species was probably introduced into northern Europe from the Mediterranean, and its occurrences on the Canary Islands and Madeira are certainly also due to introduction. However, while it occurs in North Africa, there are no records from Italy or continental Spain and only two or three from France, in western and central parts – Finistère (Blower 1987), Nièvre (Jawłowski 1933b), and possibly Vienne departments (a female). It may have been overlooked in the past because of known confusion with similar species, especially C. parisiorum and C. arborum. We have not shown on our map records from Göteborg and Piteå in Sweden, Buskerud in Norway, southern Finland, and Kiev in the Ukraine because these are from greenhouses.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.007

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 head0.025
GPT teacher head0.235
Teacher spread0.210 · 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 designObservational
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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