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Record W4395157955 · doi:10.15468/dl.8nd3e9

Occurrence Download

2019· dataset· es· W4395157955 on OpenAlexaboutno aff

Bibliographic record

VenueGlobal Biodiversity Information Facility · 2019
Typedataset
Languagees
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsnot available
Fundersnot available
KeywordsDownloadComputer scienceMathematicsWorld Wide Web

Abstract

fetched live from OpenAlex

A dataset containing 815 species occurrences available in GBIF matching the query: { "and" : [ "BasisOfRecord is Specimen", "Country is Colombia", { "or" : [ "DatasetKey is Canadian Museum of Nature Insect Collection", "DatasetKey is Colección de Entomología del Instituto de Investigación de Recursos Biológicos Alexander von Humboldt (IAvH-E)", "DatasetKey is Coleópteros de los bosques montanos del Oriente Antioqueño, Cañón del río Melcocho, en el municipio de El Carmen de Viboral, Antioquia - Proyecto Colombia BIO", "DatasetKey is Colección entomológica del Museo de Historia Natural “Luis Gonzalo Andrade” de la UPTC", "DatasetKey is Insectos en el municipio de Medina, Cundinamarca - Proyecto Colombia Bio", "DatasetKey is Escarabajos coprófagos (Scarabaeidae: Scarabaeinae) del eje cafetero Colombiano", "DatasetKey is Coleópteros de sistemas cársticos en el municipio de El Peñón, Santander - Proyecto Colombia BIO", "DatasetKey is Estudios bióticos (Plantas, Fauna Edáfica, Anfibios y Aves) en los Complejos de páramos Tota-Bijagual-Mamapacha" ] }, "HasCoordinate is true", "TaxonKey is Cryptocanthon Balthasar, 1942", "HasGeospatialIssue is false" ] } The dataset includes 815 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006384-190415153152247/datasets/export for details. Data from some individual datasets included in this download may be licensed under less restrictive terms.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.592

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 head0.016
GPT teacher head0.222
Teacher spread0.207 · 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
Published2019
Admission routes1
Has abstractyes

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