Novel approach to data analysis in cocaine-conditioned place preference
Bibliographic record
Abstract
Only a subgroup of human drug users progress from initial drug taking to drug addiction. The learned associations between the effects of the drug and the environment in which it is experienced is an important aspect of the progression to continued drug taking and drug seeking. These associations can be modeled using the conditioned place preference (CPP) paradigm, although no current method of CPP analysis allows for the identification of within-group variability among subjects. In this study, we adapted a 'criterion' method of analysis to separate 'CPP expressing' from 'non-CPP expressing' rats to study more directly within-group variability in the CPP paradigm. Male Sprague-Dawley rats were conditioned with cocaine (5, 10, 20 mg/kg) or saline in an unbiased three-chamber CPP apparatus in either a single-trial or four-trial CPP procedure. A classification and regression tree analysis of time spent in the cocaine-paired chamber established a time of 324 s spent in the cocaine-paired chamber as the criterion for cocaine CPP expression. This criterion effectively discriminated control from cocaine-conditioned rats and was reliable for rats trained in both single trial and four-trial CPP procedures. The criterion method showed an enhanced ability to detect effective doses of cocaine in the single-trial CPP procedure and a blockade of CPP expression by MK 212 (0.125 mg/kg) treatment in a subgroup of rats. These data support the utility of the criterion analysis as an adjunct to traditional methods that compare group averages in CPP.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".