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Record W6931564103 · doi:10.5281/zenodo.7292752

Insights into natal origins of migratory Nearctic hover flies (Diptera: Syrphidae): New evidence from stable isotope (δ2H) assignment analyses

2022· other· en· W6931564103 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typeother
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsWestern University
Fundersnot available
KeywordsNucleofectionHyporeflexiaArticular cartilage damageCircumstantial evidenceTSG101Proteogenomics

Abstract

fetched live from OpenAlex

Hover flies (Diptera: Syrphidae) are an important group of insects that provide a multitude of key ecosystem services including pollination and biological control, yet many of their major life history traits are not understood. Some Palearctic hover fly species are known to migrate in response to changing seasonal conditions, yet this behavior is almost entirely unrecognized in Nearctic species. At least one species, Eupeodes americanus (Wiedemann 1830), is partially migratory during autumn while Allograpta obliqua may be non-migratory, but it is unknown where these insects originate and how far they may travel. We examined natal origins of two Nearctic hover fly species, Allograpta obliqua and Eupeodes americanus, using stable hydrogen isotope (δ2H) measurements of metabolically inactive tissues (wings and legs) to derive a hover fly δ2H isoscape. While Allograpta obliqua was mostly of local origin, several Eupeodes americanus were sourced from northern latitudes in the Midwestern United States and Canada, representing travel distances of up to 3,000 km likely using seasonally favorable air currents. This phenomenon is expected to have major ecological and economic ramifications, especially in the realm of plant pollination ecology and biological control.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.321
Teacher spread0.251 · 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
Published2022
Admission routes2
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicTrace Elements in HealthFrench-language works237,207