When Should We Start Doing Research and Publishing Papers?
Bibliographic record
Abstract
Abstract Although basic statistics are covered during the Preventive Medicine posting in the majority of medical schools in India there is no attention paid to research. However, globally many leading universities encourage their undergraduates to do research. A classic example of this was in 1923 when Charles Best was an undergraduate at the University of Toronto, he together with Banting and Mcleod, discovered insulin. Banting shared the Nobel Prize that he was subsequently awarded with his student Best. Another Nobel laureate, Alan Hodgkin, won the Nobel Prize in 1972 for his work on nerve transmission that he had begun as an undergraduate in Cambridge, England.
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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 | 0.058 | 0.185 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.044 | 0.036 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.065 | 0.099 |
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".