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Record W6931525811 · doi:10.5281/zenodo.6001381

Potamites ecpleopus Cope 1876

2017· article· en· W6931525811 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicProbability and Risk Models
Canadian institutionsnot available
Fundersnot available
KeywordsTributaryAmazon rainforestDisjunctSTREAMSDistribution (mathematics)

Abstract

fetched live from OpenAlex

Potamites ecpleopus (Cope, 1876) Type-locality. Middle and upper Amazon, in Brazil and Peru, restricted by Uzzell (1966) to Río Huallaga, somewhere between Rioja, Moyobamba and Balsaspuerto. Pertinent taxonomic references. Cope (1876), Boulenger (1885), Sinitsin (1930), Burt & Burt (1931), Shreve (1935), Cunha (1961), Uzzell (1966), Peters & Donoso-Barros (1970), Sherbrooke & Cole (1972), Duellman (1978), Cunha et al. (1985), Ávila-Pires (1995), Vanzolini (1995), Ávila-Pires & Vitt (1998), Pellegrino et al. (2001), Bell et al. (2003), Castoe et al. (2004), Doan & Castoe (2005), Chávez & Vásquez (2012), Goicoechea et al. (2016). Distribution and habitat. Potamites ecpleopus is endemic to Amazonia, with an apparently disjunct distribution in western (delimited eastward by the Japurá, Purus, and Beni Rivers) and eastern Amazonia (restricted to the Tocantins –Xingu and Xingu–Tapajós interfluviums, south of the Amazon) (Fig. 15). MZUSP 64623, however, comes from the upper Comemoração River, a second order tributary of the Madeira River, an intermediary location between the western and eastern areas of occurrence. Potamites ecpleopus occurs in Brazil, Colombia, Ecuador, Peru, and Bolivia (Fig. 15). In Brazil, it is known from the states of Pará, Amazonas, Acre, Rondônia, and Mato Grosso. Potamites ecpleopus is semiaquatic and diurnal, inhabits primary and disturbed terra firme forests, where it is found close to streams (with sandy, rocky or muddy bottoms), in swampy areas, on the leaf litter or directly on rocks or mud (occasionally on trunks, branches or limbs); active specimens are either at the margin of, or partially submerged in the water, and they may also be found under logs and in holes between rocks at the edge of water (Sherbrooke 1975; Duellman 1978; Cunha et al. 1985; Dixon & Soini 1986; Ávila-Pires 1995; Vitt & Zani 1996; Vitt & Ávila-Pires 1998; Vitt et al. 1998b; 1999; Schlüter et al. 2004; Whitworth & Beirne 2011).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.002

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 head0.191
GPT teacher head0.365
Teacher spread0.173 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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