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Thalidomide: The journey from curse to boon

2023· article· en· W4381334104 on OpenAlexaboutno aff
Janvi. A. Fadnis, Amol V. Sawale, Shreyash. S. Padmawar

Bibliographic record

VenueWorld Journal of Biology Pharmacy and Health Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsThalidomideMedicineTragedy (event)Medical prescriptionFamily medicinePediatricsPsychiatryInternal medicineMultiple myelomaPharmacology

Abstract

fetched live from OpenAlex

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.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.242
GPT teacher head0.489
Teacher spread0.247 · 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 designObservational
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

Citations3
Published2023
Admission routes1
Has abstractyes

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