Comparison of Quantitative and Qualitative Dermatoglyphic Characteristics of Opium Addicts with Healthy Individuals.
Bibliographic record
Abstract
BACKGROUND: Recreational drugs have a significant impact on the lives of drug users, their close families andfriends, as well as their society. Social, psychological, biological, and genetic factors could make a personmore prone to using recreational drugs. Finger and A-B ridges (dermatoglyphics) are formed during the firstand second trimesters of fetal development, under the influence of environmental and genetic factors. Theaim of our study was to investigate and evaluate a possible link between dermatoglyphics and opium usage. METHODS: The pattern of dermatoglyphics - finger and A-B prints - obtained from a group of opium users(121 patients) was compared to those obtained from a group of opium non-users (121 patients) from Birjand,Iran. The results were analyzed using chi-square, t and Mann-Whitney tests. FINDINGS: The results showed that although A-B ridges of palms and fingers in our study group were highercompared to the control group, there was no significant difference between these groups. The only significantdifference was the fingerprint patterns of the left ring finger in the study group, which lacked the arch patternand had less loop patterns. The dominant type of fingerprint in the left ring finger was the whorl. In ouropium user group, the arch and loop fingerprint patterns were heterogeneous and significantly different incomparison with the control group (P < 0.01). CONCLUSION: These findings suggest that a genetic factor may increase the predisposition to recreational drugusage. Further research is required to confirm this possible impact of genetic factors on the addiction process.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".