Non-gaming computer use relationship to type of dream
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
A new waking influence has emerged that is becoming so widely experienced that it bears further consideration in its own right as to it’s influence on subsequent night time dreams. That is, digital life. It ranges from listening to music to texting to checking facebook status to playing video games to information checking. All of these activities are computer mediated. In this inquiry, students at a western Canadian university indicated if they had played computer games or used the computer for non-gaming purposes during the day prior to a recent dream they reported. Respondents indicated their confidence about the type of dream they reported as well their video game play habits and generic media used the day prior to the dream. There was some indication that the high end non-gaming computer use group had more lucid (females only) and control dreams but less bizarre dreams. Unlike previous research there were no differences in nightmares or bad dreams among groups. This was discussed in terms of previous video game play and dreams research.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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