Bibliographic record
Abstract
Objective: The study objectives are to identify the problems which confront renal transplant recipients( RTRS).Methodology: A descriptive study was carried out at two Teaching Hospitals with kidney transplantcenters. Surgical specialties and Al-Karama outpatients,clinics for ( RTRS) ,and three TeachingHospitals; Medical city, Al-Karama and Al-Yermok which were responsible for immunosuppressivedrugs distribution .Starting from October ,1st 2006 to the end of July 2007.To achieve the objectivesof study, a non-probability (purposive) sample of 150 ( RTRS) who were attending to the outpatientclinic of the above listed hospital were selected according to the criteria of the study sample .The finalized questionnaire contained (83) items. The content validity of the instrument wasestablished through penal of (14) experts.Reliability of the problems scales was determined by test-retest method which was estimated asaverage (r=0.76).Data was gathered by interview technique using the questionnaire format and data was analyzed byapplication of descriptive and inferential statistical methods.Results: The results of the study indicated that the ( RTRS) confront (83 ) problems and affected bythese problems with different severity level, high, moderate, and low.Recommendation: According to the results of this study, the researcher recommended that theprovision of the necessary post transplant medicines from easy to reach centers.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".