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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 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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.013
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0270.007

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 head0.048
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; 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
Published2024
Admission routes1
Has abstractyes

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