An Introduction to the Fundamentals of Cohort and Case–Control Studies
Bibliographic record
Abstract
Limitation of RCT* Complementary Aspect of Cohort and Case-Control Studies Use of a strict study protocol that is often not Usually representative of settings of routine representative of typical care medical care Exclusion of key patient populations, such May focus on vulnerable and under-represented as children, pregnant women, and elderly people populations Limited sample size May include large number of patients, especially if secondary data sources are used, thereby allowing rare events to be detected Short duration May follow patients for long periods of time (e.g., years) Evaluation of irrelevant treatment comparisons May compare several relevant therapies Outcomes measured may not be important May include any outcome that is measurable to the patient (e.g., surrogate end points) within the data source High cost Relatively low cost *These limitations apply to typical RCTs.Designing more pragmatic RCTs would also overcome many these limitations.
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 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 | 0.095 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 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".