Thalidomide: The journey from curse to boon
Bibliographic record
Abstract
The tragic spectacle of thousands of infants born with deformed arms and legs at the beginning of the 1960s stunned the entire globe. The public's memory has been permanently scarred by the sight of those young people struggling with limb deformities. The medicine thalidomide, which pregnant women use for morning sickness and insomnia, was found to be responsible for the deformities in limbs and other organs. Thalidomide was sold in over 40 nations and was authorised for prescription usage in Canada from April 1961 to March 1962. Although the true number was likely greater due to spontaneous miscarriages and stillbirths, it resulted in around 115 occurrences of deformities in this country.Due to its expulsion from the medical toolbox, this medication became a term of demeaning for many years. However, thalidomide has emerged from the darkness of unimaginable tragedy. Though under stringent restrictions, it has made a remarkable recovery and entered the current therapeutic regimen. As a result of the discovery that thalidomide and its derivatives have beneficial effects on a variety of cellular functions, they are currently recommended for the treatment of a number of diseases, including leprosy and multiple myeloma. Before returning the medication to the market, the US FDA conducted a number of clinical trials. Additionally, the deaths connected to this agent stimulated legislation that expanded patient informed consent processes, redesigned the FDA regulatory process, and required more openness from pharmaceutical companies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".