Replication Data for: How does Mindfulness Impact Thought Suppression and Emotional Regulation
Bibliographic record
Abstract
A total of 133 adults between the age range of 20-60 years were selected using purposive/snowball sampling. Data collection occurred over a month, and participants were provided useful resources for their participation. The questionnaire was circulated to 175 adults, out of which 62 were excluded due to incomplete responses. The participants were from 16 countries, which were: The United States, The United Kingdom, Australia, Canada, Czech Republic, Denmark, France, Hungary, Netherlands, Norway, Pakistan, Romania, Saudi Arabia, Sweden, Switzerland, and India. The participants in India belonged to different states and union territories which were Karnataka, Bihar, Delhi, Gujarat, Haryana, Telangana, Jharkhand, Kashmir, Uttar Pradesh, Tamil Nadu, Pondicherry, and West Bengal. Inclusion Criteria. The participants in the study were included based on the following criteria. Age. The participants had to fall in the age range of 20-60 years. Language. Due to the nature of the survey, the language compatibility was expected to be English.
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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.017 |
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".