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Record W4399131212 · doi:10.1201/9781003296492-7

Regulations in Canada

2024· book-chapter· en· W4399131212 on OpenAlexaboutno aff
Hasan Ali, Sandeep Kumar Singh, Babar Iqbal, Neeraj Sharma, Faraat Ali, Md Akbar

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

A multitude of research groups are involved in progressing drug discovery via many stages of development and transforming a drug into a potential therapeutic product. Drug regulations are of essential relevance among all of the groups engaged in the conversion of new chemical entity into a potential drugs molecule. Regulatory affairs department of a pharmaceutical company is responsible for submitting an application, scrutinizing, and tracking approval procedures for new drug substances and products, and ensuring that the approval has been renewed and extended for the time as long as the organization wishes to keep the product on the market. Like other countries, Canada has its own widely recognized regulatory body, which is Health Canada, a representative of the Government of Canada. It is responsible for the enforcement and execution of laws related to drugs and pharmaceuticals. Health Canada also regulates the pharmaceutical companies for the delivery of safe and effective drugs. Health Canada actively contributes to ensure that the Canadian public has easy access to safe and effective drugs. This chapter focuses on the fundamentals of drug–related and drug product-related regulatory processes, registration, clinical trials application, enforcement, compliance, and other legislation associated with the drug and drug-related products and their authority under Health Canada’s command.

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.088
Threshold uncertainty score0.636

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0120.004
Scholarly communication0.0080.002
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0530.010

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 head0.077
GPT teacher head0.336
Teacher spread0.260 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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