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Record W3127687603 · doi:10.5399/osu/cat_osac.5.1.4647

Oregon Bee Atlas: native bee findings from 2018

2021· article· en· W3127687603 on OpenAlexaff
Lincoln R. Best, Christopher Marshall, Cody Feuerborn, Sarah Kincaid, Andony Melathopoulos, Samuel V.J. Robinson

Bibliographic record

VenueCATALOG OREGON STATE ARTHROPOD COLLECTION · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFaunaBiologyEcology

Abstract

fetched live from OpenAlex

The Oregon Bee Atlas is a new volunteer-led effort to characterize the bee fauna of Oregon State by collecting, preparing, and databasing native bee species and capturing plant host records. In 2018, volunteers collected 11,044 bee specimens across 33 Oregon counties, representing 179 unique bee species, and 32 unique bee genera. Specimens were collected from a total of 310 unique flowering plant genera, resulting in one of the largest state-level databases of bee-host plant interactions. Volunteers produced valuable occurrence records for species poorly known for the State, and species of conservation concern. The 2018 efforts constitute a proof-of-concept of a specimen-focused volunteer native bee survey.

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)0.001
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: none
Teacher disagreement score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.004

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 head0.028
GPT teacher head0.218
Teacher spread0.190 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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