Interactive evolution instead of default parameters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tools for processing biological data often have many parameters, but most users simply use the default settings. Such software often has a large number of controls or user specified parameters. This means that there can be problems with teaching users to use even standard bioinformatic tools effectively. This study prototypes a technique called a show-me-more interface that uses human-in-the-loop evolution to permit an untutored user to operate a complex software tool that designs images of flowers. This task is intended to permit research on managing complex parameters for users that do not understand them without the added complexity of working with biological data. Users are given two specific and two nonspecific tasks and the results of their design efforts are displayed and discussed. The basic concept of show-me-more control has broad applications for permitting casual users to manipulate complex tools in a simple and transparent manner. Careful design can minimize the number of clicks needed for a user to reanalyze data, reducing the potential for user fatigue and attendant error.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it