Randomized Controlled Trials and Challenge Trials: Design and Criterion for Validity
Bibliographic record
Abstract
This article is the third of six articles addressing systematic reviews in animal agriculture and veterinary medicine. This article provides an overview of clinical trials, both randomized controlled trials (RCTs) and challenge trials, where the disease outcome is deliberately induced by the investigator. RCTs are not the only study design used in systematic reviews, but are preferred when available as the gold standard for evaluating interventions under real-world conditions. RCTs are planned experiments, which involve diseased or at-risk study subjects and are designed to evaluate interventions (therapeutic treatments or preventive strategies, including antibiotics, vaccines, management practices, dietary changes, management changes or lifestyle changes). Key components of the RCT are the use of one or more comparison (control) groups and investigator control over intervention allocation. Important design features in RCTs include as follows: how the population is selected, approach to allocation of intervention and control group subjects, how allocation is concealed prior to enrolment of study subjects, how outcomes are defined, how allocation to group is concealed (blinding) and how withdrawals from the study are managed. Guidelines for reporting important features of RCTs have been published and are useful tools for writing, reviewing and reading reports of RCTs.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.875 | 0.619 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.125 | 0.010 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".