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Record W6893380371 · doi:10.5281/zenodo.15755476

Castor canadensis Kuhl 1820

2020· article· en· W6893380371 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsCastor canadensisBeaverHabitatNearctic ecozone

Abstract

fetched live from OpenAlex

Castor canadensis Kuhl, 1820 American Beaver Castor canadensis was once widespread across the state. Dramatic declines due to trapping resulted in Blair (1939) suggesting that the species was extirpated from the state. Since that time, populations have increased statewide. Roehrs et al. (2012) reported a new specimen county record for McCurtain County. New specimen county records are reported for nine counties, including Garfield, Muskogee, Nowata, Oklahoma, Osage, Rogers, Seminole, Tulsa, and Washington. Specimen records (27).—Garfield County (1): Jim Powell's farm, N of Enid, 1 (UCOCV-MAM 2047). Muskogee County (1): ca 1.6 km SE Fort Gibson, T15N, R19E, Sec 13, NE 1/4, 1 (OMNH 14555). Nowata County (3): Verdigris River, 3 (ISM 693497, 693502, 693504). Oklahoma County (4): no specific locality, 1 (OMNH 66099); jct I-35 and I-240, Oklahoma City, 1 (OMNH 19568); Memorial Rd, ca 0.3 km W of Portland Ave, Oklahoma City, 1 (UCOCV-MAM 4182); on E Hefner Rd between N Douglas Blvd and N Canadian River, 1 (UCOCV-MAM 4395). Osage County (11): Pond Creek, 9 (ISM 693495–693496, 693499–693500, 693503, 693505–693507, 693509); Friend Ranch, 2 (ISM 693501, 693508). Rogers County (1): 5.6 km SW Inola, 1 (MSB 113402). Seminole County (2): 4 km NW Maud, 2 (OMNH 17769- 17770). Tulsa County (1): Tulsa, 1 (NMMNH 3866). Washington County (3): no specific locality, 3 (ISM 692975, 692984, 693498).

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 score0.173
Threshold uncertainty score0.344

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.040
GPT teacher head0.202
Teacher spread0.163 · 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
Published2020
Admission routes1
Has abstractyes

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