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Record W6931038466 · doi:10.5281/zenodo.3793033

Oligota parva Kraatz 1862

2008· article· en· W6931038466 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2008
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsSt. Francis Xavier UniversityNova Scotia Hospital
Fundersnot available
KeywordsLittoral zonePredationIndian oceanTaxonomy (biology)

Abstract

fetched live from OpenAlex

Oligota parva Kraatz, 1858 PRINCE EDWARD ISLAND: Kings Co.: Launching, 26.VIII.2003, C.G. Majka, ocean beach: under coastline drift at the top of the littoral zone, (4, CGMC). Oligota parva (Fig. 2) is newly recorded in Canada (Fig. 12). It has been previously recorded from California, Massachusetts, Missouri, and Texas (Moore and Legner 1975). It has been introduced to the western Palearctic and northern Africa and is now widespread there (Horion 1967; Smetana 2004). It is found in compost, on dung, in fermenting materials, in old hay and grass, and in other decomposing situations (Horion 1967). The ecology of Oligota species are not well known, however, at least some species prey on mites (Frank et al. 1992). While O. parva has not previously been reported as a beach drift species, all the specimens collected on Prince Edward Island were found in this habitat. One European species, Oligota pusillima Gravenhorst, 1806 has been recorded in decaying seaweed (Fowler 1888; Moore and Legner 1975). Other characteristic beach drift species collected together with O. parva at Launching (PEI), include Atheta acadiensis, Strigota ambigua (see below) [Staphylinidae], Hypocaccus fraternus (Say, 1825) [Histeridae], Monotoma producta LeConte, 1855 [Monotomidae], and Blapstinus metallicus (Fabricius, 1801) [Tenebrionidae].

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0280.009

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 head0.085
GPT teacher head0.307
Teacher spread0.222 · 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
GenreEmpirical

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
Published2008
Admission routes2
Has abstractyes

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