Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this research was to compare the personality characteristics and driving behavior between the risky and safe drivers of Marivan Township.The statistical population included all drivers of Marivan township who had certification in 2014 that 225 persons of the statistical selected drivers were replaced in two groups of safe drivers (lack of accident and using of car insurance coupon) and risky drivers (accident record and using of insurance coupon) purposefully by referring to the insurance centers and according to the available sampling.The research variables were assessed through emotional intelligence questionnaire of Brad Berry & Jane Greaves and the questionnaire of Manchester driving behavior.The findings of the research questionnaires were analyzed by using of independent T-test and Hotelling , s T-test.The results of the comparative analysis showed, there was meaningful difference between the relations management and social awareness in risky and safe drivers.The rate of mistakes, errors, intentional and unintentional violations in risky drivers was more than the safe drivers and this difference was meaningful statistically.The results of this research showed that the personality characteristics and psychological components (emotional intelligence and driving behavior) have been different between the drivers and therefore these factors should be also considered in giving the certification to the drivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.980 | 0.998 |
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 it