MétaCan
Menu
Back to cohort
Record W4413118144 · doi:10.1093/jaoacint/qsaf073

Use of a Spectrophotometric Method for the Detection of Adulterants in Commercial Fulvic Acid Products

2025· article· en· W4413118144 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

VenueJournal of AOAC International · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHumic Substances and Bio-Organic Studies
Canadian institutionsHumber Polytechnic
FundersUniversity of Oxford
KeywordsChromatographyFulvic acidChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Numerous products manufactured from non-humic sources have flooded the market claiming to be fulvic acids. The challenge is finding an easy method to distinguish between products containing genuine fulvic fractions and those containing adulterants. UV spectrophotometry has been widely used to study the fulvic fraction extracted from humic substances, with multiple metrics derived from UV absorption spectra developed and implemented by researchers. OBJECTIVE: Leverage ten indices that are characteristic features of the UV spectra of hydrophobic fulvic acids to differentiate products containing authentic fulvic fractions from those containing adulterants. METHODS: Fulvic fractions were diluted to 5 ppm carbon and UV spectra were obtained. Spectra were normalized and analyzed to calculate 10 different indices. The percent difference between the index values of the product and the corresponding index values for the Suwannee River fulvic acid (SRFA) and Pahokee peat fulvic acid (PPFA) standards were calculated. An equally weighted average for all 10 indices was calculated and a 70% cutoff value was used for the average percent error as a screening tool to distinguish products containing fulvic fractions from adulterants. RESULTS: Fifty-four test samples were analyzed, with nine samples being analyzed by two different laboratories using the established method. Fourteen of the 25 commercial products studied were found to contain fulvic fractions. Increased metal ion concentration within the investigated range did not impact the average percent error calculated, nor did varying the total organic carbon concentrations of the test portions within the range of 1-10 ppm. CONCLUSION: The method investigated could be a suitable screening tool for most commercial products and is capable of accurately distinguishing products that contain fulvic fractions. HIGHLIGHTS: The method accurately found all 11 fulvic fractions isolated from known humic substances as fulvic, and all 11 test samples prepared from non-humified materials as non-fulvic.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.072

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.044
GPT teacher head0.300
Teacher spread0.256 · 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