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Record W3031551703 · doi:10.1111/add.15107

Moving forwards with the standard THC unit

2020· letter· en· W3031551703 on OpenAlexaboutno aff
Tom P. Freeman, Valentina Lorenzetti

Bibliographic record

VenueAddiction · 2020
Typeletter
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
FundersSociety for the Study of Addiction
KeywordsCannabisDronabinolWorkgroupCannabinoidUnit (ring theory)MedicineDelta-9-tetrahydrocannabinolEffects of cannabisSynthetic cannabinoidsTetrahydrocannabinolPsychologyPsychiatryComputer science

Abstract

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There is international support for a standard tetrahydrocannabinol (THC) unit, which could improve the precision with which we understand, regulate and communicate dose-related risks and benefits to consumers. Implementing the standard THC unit in legal recreational cannabis markets would represent an important step forward. We appreciate the commentaries [1-4] which support our proposal for a standard THC unit [5] and raise insightful points for progressing with this initiative. Chester et al. [1] outline the importance of experimental cannabinoid studies for informing the standard tetrahydrocannabinol (THC) unit. Our proposal for a 5-mg THC unit was informed by experimental studies showing that this low dose produces intoxication in infrequent users with minimal risk of adverse acute effects [5]. Moving forward, experimental cannabinoid studies can quantify dose–response effects of THC unit consumption on acute harms and benefits, such as driving performance [6]. Experimental studies should include a wide range of THC unit doses to capture real-world consumption and contrasting directions of effect at low and high doses [2]. Volkow & Weiss [3] and the NIDA Cannabis Policy Research Workgroup [7] highlight the value of a standard THC unit for advancing the understanding of the long-term effects of cannabis use. Large-scale longitudinal cohort studies (e.g. the Adolescent Brain Cognitive Development study) are now enhancing time-line follow-back methods using pictorial assessment of cannabis type and quantity [8]. Where available, legal cannabis products with known standard THC unit content could increase precision when estimating the long-term effects of cannabis use on brain, cognitive and mental health outcomes throughout the life-span. Filbey [2] and Volkow & Weiss [3] suggest that standard units of dose could also be applied to medicinal use of cannabis and cannabinoids. We agree that this could be helpful for informing patients and clinicians if supported by robust scientific evidence. As the safety and efficacy of cannabinoids for medicinal purposes differ from effects during recreational use, care would be needed when communicating relative risks and benefits among different populations. As a priority, standard THC units should be implemented in legal recreational cannabis markets, such as those in Canada, Uruguay and some US states. As pointed out by Hammond [4], a standard THC unit would represent a considerable improvement to the status quo, despite differences in the time–course and effect profile of certain products [1]. Current dosing information for oral (mg THC) and inhaled (% THC) products are poorly understood by consumers [9] and are difficult to compare with each other. Listing the number of doses per package substantially improves consumer understanding [9] and fulfils the need for clearer dosing information [10]. In conclusion, a standard THC unit is necessary to advance and harmonize scientific research, product regulation and consumer understanding of cannabis use and its consequences. Implementing standard THC units in legal recreational cannabis markets would represent an important step towards this goal. None. T. F. is funded by a Senior Academic Fellowship from the Society for the Study of Addiction. The funder had no role in the writing of the report or the decision to submit for publication. Tom Freeman: Conceptualization-lead; writing-original draft-lead; writing-review & editing-equal. Valentina Lorenzetti: Conceptualization-supporting; writing-review & editing-equal.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.094
Threshold uncertainty score0.991

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 integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations8
Published2020
Admission routes1
Has abstractyes

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