Palladium alloy model systems forunderstanding the surface properties of Pd-based membranes and catalysts
Bibliographic record
Abstract
<i>Background:</i> Prior research has established that Adverse Childhood Experiences (ACEs) predict harmful alcohol use outcomes. However, underlying mechanisms that could explain these associations are less clear. The present study examined if ACEs are indirectly related to alcohol negative consequences through their associations with distress tolerance and drinking to cope. <i>Method:</i> A sample of 3,763 (71.9% female) college students who drink alcohol from seven countries (U.S., Argentina, Canada, Uruguay, Spain, South Africa, and England) completed online surveys. Path analysis was performed within the whole sample testing the serial unique associations between ACEs→distress tolerance→drinking to cope→negative alcohol-related consequences. Multi-group analysis was performed to determine if the proposed pathways were invariant across gender and countries. <i>Results:</i> Both distress tolerance and drinking to cope uniquely accounted for the relationship between ACEs and negative alcohol-related consequences. Additionally, a significant double-mediation effect was found illustrating that a higher endorsement of ACEs was associated with lower distress tolerance, which in turn was associated with higher drinking to cope, which in turn was associated with more negative alcohol-related consequences. These effects were invariant across countries and gender groups. <i>Conclusions:</i> These findings provide support for the relevance of distress tolerance and coping motives as potential factors in linking ACEs to problematic alcohol use across nations. Our data are consistent with the idea that intervening on distress tolerance and drinking motives could mitigate downstream alcohol-related consequences related to ACEs in college student populations around the world.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".