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Record W2382680259

Study on the Diversity of Common Medicinal Plants in Zhang County of Gansu Province

2013· article· en· W2382680259 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNorthern Horticulture · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and Biological Activities
Canadian institutionsScience North
Fundersnot available
KeywordsMedicinal plantsLianaBiologyGeographyBotanyOrnamental plantAgroforestryTraditional medicine
DOInot available

Abstract

fetched live from OpenAlex

Zhang county is known as 'the millennium rural medicine',knowing the local medicinal resource is the basis for developing medicinal plants.The common resources of medicinal plants in Zhang county based on literature study and expeditionary survey were calculated in this study.The results showed that there were 385 species of medicinal plants belonging to 275 genera and 99 families,in which 304 species were herbs,48 species were shrubs,28 species were magaphanerophytes,5 species were lianas;dominant families were Composiatae,Rosaceae,Ranunculaceae etc,and dominant genera were Artemisia and Polygonum etc.Many parts of medicinal plants could be used as medicinal materials,which were mostly grasses and roots.Therefore,consideration to update of resources should be given to make sure regeneration of resources when collecting the medicinal plants and lay the foundation for the sustainable utilization of medicinal plant.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.139
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.211
Teacher spread0.184 · 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