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Record W7132965979

Identification business plan: commercialization and export of medicinal cannabis to Toronto - Canadá

2020· dissertation· es· W7132965979 on OpenAlexaboutno aff
Laura Daniela Toro Díaz

Bibliographic record

VenueLumieres - Repositorio institucional Universidad de América · 2020
Typedissertation
Languagees
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsCommercializationTariffIdentification (biology)Production (economics)NegotiationGovernment (linguistics)Recreation
DOInot available

Abstract

fetched live from OpenAlex

The cannabis plant has been used throughout history by many cultures, for its medicinal properties, although it is worth remembering that in some places it has been misused when used for recreational and illegal purposes, so that today some countries forbid it. We are in an era where every day advances in technology and research are seen, and even more so in medicine, this being a great advantage for the economic opening and development of the country, due to the ease of having crops and production and subsequent transformation of this plant. Canada is chosen as the destination to export for its stable economy, the elimination of tariff barriers for this type of product, for its customs efficiency and also that thanks to the free trade agreement many negotiations with this country can be carried out from now on and thus managing to increase the economic competitiveness of Colombia.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.014
GPT teacher head0.289
Teacher spread0.275 · 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.

Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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