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Record W6949415522 · doi:10.5281/zenodo.15174527

Table 3 in Coleoptera of Brazil: what we knew then and what we know now. Insights from the Catálogo Taxonômico da Fauna do Brasil

2024· dataset· en· W6949415522 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsCanadian Museum of Nature
Fundersnot available
KeywordsScarabaeidaeFaunaTable (database)BATESKarel

Abstract

fetched live from OpenAlex

Table 3. Top ten authors with the most valid names for species recorded from Brazil. AuthorNationality Family Number of species Years of publicationMaurice Pic 1 (1866–1957)FrenchAderidae, Anthicidae, Archeocrypticidae, Artematopodidae, Byrrhidae, Callirhipidae, Cantharidae, Chelonariidae, Chrysomelidae, Ciidae, Cleridae, Cneoglossidae, Dermestidae, Endomychidae, Georissidae, Lampyridae, Limnichidae, Lycidae, Lymexylidae, Megalopodidae, Melandryidae, Meloidae, Melyridae, Mordellidae, Mycteridae, Oedemeridae, Phengodidae, Ptilodactylidae, Ptinidae, Ripiphoridae, Salpingidae, Scirtidae, Scraptiidae, Staphylinidae, Tenebrionidae and Zopheridae1,7941894–1956Carl Henrich Boheman 2 (1796–1868)SwedishAnthribidae, Belidae, Brentidae, Buprestidae, Cantharidae, Carabidae, Cerambycidae, Chrysomelidae, Coccinellidae, Curculionidae, Histeridae, Hydrophilidae, Mordellidae, Nitidulidae, Ptilodactylidae, Scarabaeidae, Staphylinidae and Tenebrionidae1,3091829–1862Jan Karel Bechyné 3 (1920–1973)CzechChrysomelidae1,229*1944–1983Carl Fiedler 4 (1864–1955)GermanCurculionidae1,0741932–1954Ubirajara Ribeiro Martins 5 (1932–2015)BrazilianCerambycidae, Disteniidae and Erotylidae1,008*1959–2016Henry Walter Bates 6 (1825–1892)EnglishCarabidae, Cerambycidae, Chrysomelidae, Disteniidae, Endomychidae, Geotrupidae, Hybosoridae, Megalopodidae, Melolonthidae, Scarabaeidae and Tenebrionidae7381861–1891Thomas Lincoln Casey 8 (1857–1925)AmericanCoccinellidae, Curculionidae, Melolonthidae and Staphylinidae6571890–1922David Sharp 7 (1840–1922)EnglishAttelabidae, Bothrideridae, Brentidae, Carabidae, Chrysomelidae, Dytiscidae, Elmidae, Epimetopidae, Hydrochidae, Hydrophilidae, Laemophloeidae, Limnichidae, Melolonthidae, Monotomidae, Nitidulidae, Noteridae, Staphylinidae and Zopheridae6231874–1905Alphonse-Adrien Hustache 1 (1872–1949) FrenchAttelabidae, Belidae and Curculionidae6111922–1951Maria Helena Mainieri Galileo (b. 1950) BrazilianCerambycidae and Disteniidae535*1977–2018 *Some species-group names published with co-authors. 1 Constantin (1992); 2 Stål (1869); 3 Anonymous (1974); 4 Groll (2016b); 5 Galileo and Santos-Silva (2015); 6 Ferreira (2004); 7 Smetana and Herman (2001).

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 categoriesScholarly communication, 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 score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.006

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 head0.048
GPT teacher head0.289
Teacher spread0.241 · 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
Published2024
Admission routes1
Has abstractyes

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