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Record W4394473006 · doi:10.6084/m9.figshare.19915000

A pharmacophylogenetic study on two Artemisia species (Artemisia argyi and Artemisia indica) via multi-perspective analysis

2022· dataset· en· W4394473006 on OpenAlexaff
Zhanhu Cui, Siqi Li, Jiayin Chang, Erhuan Zang, Qian Liu, Baochang Zhou, Chao Li, Mengzhi Li, Xianzhang Huang, Zhongyi Zhang, Minhui Li

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsArtemisiaBotanyTraditional medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Positive and Negative Ion metabolism datas of <em>Artemisia argyi</em> and <em>Artemisia indica</em> at different stages (LC-MS) . <em>A. argyi</em> and <em>A. indica</em> were collected during the growing season of 2020 from an experimental field in Nanyang County (33°03’6.56” N, 112°49’36.91” E), Henan Province, China. <em>A. argyi</em> and <em>A. indica</em> leaves were obtained at three different growth stages: the early stage (April 6, 2020), middle stage (May 16, 2020), and later stage (June 26, 2020) .Freeze-dried leaves were crushed using a mixer mill for 1.5 min at 30 Hz. Then, 100 mg powder was extracted overnight at 4 °C using 1.0 mL 70% aqueous methanol. The extracts were filtered and analyzed using an ultra-performance liquid chromatography-electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) system (UPLC SHIMADZU Nexera X2; MS, Applied Biosystems 4500 Q TRAP). The analytical conditions were as follows: UPLC column, Agilent SB-C18 (1.8 µm, 2.1 mm×100 mm); solvent system, water (0.1% formic acid), acetonitrile (0.1% formic acid); gradient program, 95:5 v/v at 0 min, 5:95 v/v at 9.0 min, 5:95 v/v at 10.0 min, 95:5 v/v at 10.1 min, 95:5 v/v at 14 min; flow velocity, 0.35 mL/min; column oven, 40 °C; injection volume, 4 μL. The effluent was connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS. The ESI source operation parameters were as follows: ion source, turbo spray; temperature, 550 °C; ion spray voltage, 5500 V/-4500 V; ion source gas I, gas II, and curtain gas were set at 50, 60 and 25.0 psi, respectively. Instrument tuning and mass calibration were performed with 10 and 100 μmol/L polypropylene glycol solutions in the triple quadrupole (QQQ) and linear ion trap (LIT) modes, respectively. The declustering potential and collision energy for individual multiple reaction monitoring (MRM) transitions were determined. A specific set of MRM transitions was monitored for each period according to the metabolites eluted during this period. Metabolite analyses were performed according to the reported method.Based on the self-built database MWDB (Metware Biotechnology Co., Ltd. Wuhan, China), and a public database of metabolite information, MS was used for qualitative and quantitative analysis of the samples’ metabolites.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.4560.000

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 head0.043
GPT teacher head0.291
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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