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Record W6929032070 · doi:10.4224/crm.2021.hemp-1

HEMP-1: Certified Reference Material of dried, ground hemp

2021· other· en· W6929032070 on OpenAlexaff

Bibliographic record

VenueNRC Digital Repository · 2021
Typeother
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCertified reference materialsCertificationMatrix (chemical analysis)Quality (philosophy)Reference dataQuality standard

Abstract

fetched live from OpenAlex

HEMP-1 is a certified reference material (CRM) designed for use in method development, validation, and quality control for the analysis of cannabinoids in cannabis and hemp. While cannabinoid solution reference standards are appropriate for instrument calibration, matrix CRMs such as HEMP-1 can help validate entire methods, from sampling, extraction, clean-up, and instrumental analysis. Certified values for the mass fraction of cannabinoids in HEMP-1 have been established.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0350.026

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2021
Admission routes1
Has abstractyes

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