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Record W1001297949 · doi:10.1093/jaoac/89.6.1483

Preparation and Characterization of a Suite of Ephedra-Containing Standard Reference Materials

2006· article· en· W1001297949 on OpenAlexaff
Katherine E. Sharpless, David L. Anderson, Joseph M. Betz, Therese A. Butler, Stephen G Capar, John Cheng, Catharine Fraser, Graeme J. Gardner, Martha L. Gay, Daniel W. Howell, Toshihide Ihara, Mansoor A. Khan, Joseph Lam, Stephen E. Long, Margaret McCooeye, Elizabeth A. Mackey, William R. Mindak, Staci Mitvalsky, Karen E. Murphy, Agnes NguyenPho, Karen W. Phinney, Barbara J. Porter, Mark Roman, Lane C. Sander, Mary B. Satterfield, Christine Scriver, Ralph E. Sturgeon, Jeanice B. Thomas, Robert D. Vocke, Stephen A. Wise, Laura J. Wood, Lu Yang, James H. Yen, George C. Ziobro

Bibliographic record

VenueJournal of AOAC International · 2006
Typearticle
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFood and drug administrationEphedrineCaffeineTraditional medicineChemistryMedicinePharmacology

Abstract

fetched live from OpenAlex

The National Institute of Standards and Technology, the U.S. Food and Drug Administration, Center for Drug Evaluation and Research and Center for Food Safety and Applied Nutrition, and the National Institutes of Health, Office of Dietary Supplements, are collaborating to produce a series of Standard Reference Materials (SRMs) for dietary supplements. A suite of ephedra materials is the first in the series, and this paper describes the acquisition, preparation, and value assignment of these materials: SRMs 3240 Ephedra sinica Stapf Aerial Parts, 3241 E. sinica Stapf Native Extract, 3242 E. sinica Stapf Commercial Extract, 3243 Ephedra-Containing Solid Oral Dosage Form, and 3244 Ephedra-Containing Protein Powder. Values are assigned for ephedrine alkaloids and toxic elements in all 5 materials. Values are assigned for other analytes (e.g., caffeine, nutrient elements, proximates, etc.) in some of the materials, as appropriate. Materials in this suite of SRMs are intended for use as primary control materials when values are assigned to in-house (secondary) control materials and for validation of analytical methods for the measurement of alkaloids, toxic elements, and, in the case of SRM 3244, nutrients in similar materials.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.225

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 head0.015
GPT teacher head0.331
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2006
Admission routes1
Has abstractyes

Explore more

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