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Record W2959373651 · doi:10.3897/bdj.7.e37569

Integrating multiple sources of biodiversity information greatly expands the range of a rare species of Hymenoptera (Vanhorniidae)

2019· article· en· W2959373651 on OpenAlexaboutno aff
Joshua Hogan, Amber Bass, Y. Miles Zhang, Barbara J. Sharanowski

Bibliographic record

VenueBiodiversity Data Journal · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityGeographyRange (aeronautics)Distribution (mathematics)HymenopteraArchaeologyEcologyLibrary scienceBiologyEngineeringComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Crawford is the only species of Vanhorniidae that occurs in North America. This species is rarely collected and thus the distribution is not well documented. Intending to uncover a more accurate range of this species, we assembled collection records from museums, personal collections and citizen science projects. Many of these records were non-digitised and had to be personally requested. NEW INFORMATION: to include nine new provinces and states: Manitoba, Connecticut, Oregon, Mississippi, Missouri, New Hampshire, New Jersey, Texas and Wisconsin. Although Quebec has been listed as a previous locality, the recorded province was mislabelled, so Quebec is now also officially a provincial record.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.404
Threshold uncertainty score0.804

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0170.021
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.065
GPT teacher head0.194
Teacher spread0.129 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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