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Record W4283261474 · doi:10.18433/jpps32911

Progress and Prospects of Research Ideas and Methods in the Network Pharmacology of Traditional Chinese Medicine

2022· review· en· W4283261474 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2022
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsTraditional Chinese medicineModernization theoryEngineering ethicsSystems pharmacologyField (mathematics)Clinical pharmacologyManagement scienceMedicinePharmacologyTraditional medicineAlternative medicinePolitical scienceEngineeringDrugLaw

Abstract

fetched live from OpenAlex

In recent years, the emerging network pharmacology has been extensively applied to the field of traditional Chinese medicine and has made great contributions to the modernization of TCM. Therefore, this paper provides an overview of the progress of research ideas and methods in the network pharmacology in the last few years in the field of traditional Chinese medicine and presents insights into future research methods and ideas in the network pharmacology. Problems with the current network pharmacology are discussed and prospects of its future development are put forward.

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)0.042
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0420.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.005
Science and technology studies0.0010.010
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.538
GPT teacher head0.667
Teacher spread0.129 · 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