VLT laboratory 1 Against the Odds: Establishment of a Video Lottery Terminal Research Laboratory in a Naturalistic Setting
Bibliographic record
Abstract
The Dalhousie Gambling Laboratory was founded in 1997. It occupies two rooms in the Psychology wing of the Life Sciences Centre at Dalhousie University. One of these is a standard laboratory with computers, files, telephone, etc. The other is a “bar-lab ” complete with a bar, bar stools, a television, and two video lottery terminals (VLTs) of a sort found in bars throughout Nova Scotia. On entering the bar-lab, participants encounter brightly coloured walls, beer posters, music videos, and in some studies they are invited to purchase beverages from the bar (including beer and mixed drinks) as in a real-life bar situation. In most studies, participants are free to play the VLTs using money out of their own pockets, keeping any winnings they might obtain. Electronic control of the machines is maintained by the Atlantic Lottery Corporation computer in Moncton, New Brunswick, and the odds of winning or losing on the bar-lab VLTs are the same as on all other machines appearing in Nova Scotia. Collaborators/Areas of Research Focus. Three Ph.D. level psychologists with distinct areas of expertise are collaborating on several different applied and theoretical research issues in this laboratory. Dr.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".