Bibliographic record
Abstract
escriptive studies (also known as observational studies) are considered "natural" experiments, where the investigator lets nature take its course.Such studies may provide information on the effect of a treatment, prevention, or other exposures.The objective of an observational study is to determine the relationship between an exposure and an outcome with validity and precision while minimizing the use of resources.There are two common types of observational studies: cohort and case-control studies.Several other study designs are available and include cross-sectional and ecologic studies.Experimental study designs such as the classical randomized controlled trials are often considered the most robust method to test hypotheses (i.e., prove causation).In many instances, however, this may not be feasible and alternative study designs are required.Descriptive studies fill this role by attempting to answer the "W's": why, where, who, what, and when.Although they cannot prove or disprove a hypothesis, they can demonstrate a relationship or association. 1 The conduct and results of such studies may then inform the development of more robust randomized controlled trials.
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 | 0.260 | 0.574 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.015 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier 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".