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Record W4394187296 · doi:10.6084/m9.figshare.7719398

Sympatric speciation in the Simuluim arcticum complex (Diptera: Simuludae)

2019· dataset· en· W4394187296 on OpenAlexaboutno aff
Grant Hokit

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicDiptera species taxonomy and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsSympatric speciationGenetic algorithmBiologyZoologyEcology

Abstract

fetched live from OpenAlex

Five separate data sets were included in our analyses: Alaska (Shields and Procunier 1982), Montana, Idaho, and eastern Washington (Shields 2013; Shields 2014; Shields and Shields 2017 and Shields, unpub. data); throughout the range of S. arcticum (Conflitti et al. 2016); western Canada (Procunier, unpub.); and throughout the range of S. arcticum (Adler et al. 2004. Locations for 299 sites were determined with varying accuracy. There were 125 sites associated with recent collections using GPS capture that have an accuracy of plus or minus 5 m. There were 90 legacy sites with good location descriptions with coordinates captured with Google Earth that we are confident are within 1 km of the collection location. Finally, 84 sites had poor location descriptions often listing only a county. We used the centroid of the county location for these sites resulting in a spatial accuracy of approximately 100 km. Both the GPS coordinates and the Google Earth capture location used the datum WGS 1984. Locations for each site along with associated sibling species and cytotypes were used to create an attribute table.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.007

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 head0.101
GPT teacher head0.267
Teacher spread0.167 · 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
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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