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Record W2775609832 · doi:10.5061/dryad.c9b25/10

Bayenv output file

2015· dataset· en· W2775609832 on OpenAlexaboutno aff
Rena M. Schweizer, Bridgett M. vonHoldt, Ryan J. Harrigan, Marco Musiani, David W. Coltman, John Novembre, Robert K. Wayne

Bibliographic record

VenueDRYAD · 2015
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSeasonalityPrecipitationEnvironmental scienceRadarQuarter (Canadian coin)Metric (unit)StatisticsMathematicsGeographyMeteorologyComputer scienceEngineeringArchaeologyOperations management

Abstract

fetched live from OpenAlex

Results file from Bayenv for 94 individuals in six populations for 12 environmental variables. File is the matrix of bayes factors after averaging across ten independent runs. Each row represents a SNP, and each column contains the bayes factor for each environmental variable. BIO1: annual mean temp., BIO2: mean diurnal temp. range, BIO4: temp. seasonality, BIO5: max. temp. of warmest month, BIO6: min. temp. of coldest month), BIO12: annual precipitation, BIO15: precipitation seasonality, BIO19: precipitation of coldest quarter, LC: land cover metric, NDVIM: normalized difference vegetation index, TREE: percentage tree cover, and SRTM: shuttle radar topography metric.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.063
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0740.011

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 head0.036
GPT teacher head0.213
Teacher spread0.177 · 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; both teacher heads agree on what is shown here.

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
Published2015
Admission routes1
Has abstractyes

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