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Record W3100667770 · doi:10.22488/okstate.20.100002

A Floristic Inventory of the John W. Nichols Scout Ranch, Canadian County, Oklahoma

2019· article· en· W3100667770 on OpenAlexaboutno aff
Adam Ryburn, Abby Crosswhite

Bibliographic record

VenueOklahoma Native Plant Record · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFloristicsGeographyArchaeologyForestryEnvironmental protectionEcologyBiology

Abstract

fetched live from OpenAlex

We conducted a vascular plant survey of the John Nichols Scout Ranch in southeastern Canadian County, Oklahoma, during the growing seasons of 2017 to 2019.Vouchered specimens were collected for 152 species in 116 genera and 49 families.The largest families represented were the Asteraceae (37 species), Poaceae (19), and Fabaceae (17).No rare species currently being tracked by the Oklahoma Natural Heritage Inventory were encountered.Twenty of the species collected were not native to the United States, of which six (Lonicera japonica, Lespedeza cuneata, Bothriochloa ischaemum, Bromus tectorum, Sorghum halepense, and Tamarix chinensis) are considered invasive.Three tree species (Pinus taeda, Pistacia chinensis, and Taxodium distichum) were planted in developed areas of the ranch.Species richness appears to be low when compared to surveys of similar size.We suggest that the adjacent properties used for agriculture and housing development have influenced the number of species of this suburban wilderness.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.202
Teacher spread0.179 · 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
Published2019
Admission routes1
Has abstractyes

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