Temperature effects on polygraph detection of concealed information
Bibliographic record
Abstract
Thermoregulatory influences on electrodermal and cardiovascular activity may interfere with the detection of concealed information using a polygraph. This possibility was assessed by means of a mock terrorism scenario. Seventy-two participants were assigned to either a guilty or an innocent role. They were given a polygraph test at one of three ambient temperatures: 10°C, 22°C, or 34°C. Among guilty participants, electrodermal and cardiovascular measures were least effective at 10°C. Electrodermal results were optimal at 22°C, whereas cardiovascular results were optimal at 34°C. Among innocent participants, the effectiveness of these same measures was not affected by ambient temperature. Temperature had no significant impact on respiration results within the guilty or the innocent groups. Taken together, these findings have implications for those who use polygraphs in uncontrolled testing environments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".