Usage of Electronics Information Resources by Selected Government Medical College Library Faculties and Post Graduate Students Affiliated To Rajiv Gandhi University Health Science Karnataka : A Case Study
Bibliographic record
Abstract
The paper focuses on the use of electronic information resources by the faculty members and P.G. Students of selected medical college libraries in Hyderabad-Karnataka region. The investigator has distributed questionnaires to the faculty members (90) and P.G. Students (90) total 180, out of which faculty members (75), P.G students (75) total 150 (83.33%) questionnaires were received back. The findings of the study shows that majority (85%) of the respondents purpose of accessing internet for data communication (sending and receiving E-Mail, Chat, Net Phone) followed by 51% of them access internet for purpose retrieve medical case history. The result also indicates that majority (88%) of the respondents use electronic information resources for supporting teaching activities and 61% for journal club purpose. Some of the considerable numbers of respondents (85%) are aware of electronic information resources by personal communication with friends, subject experts and resource persons.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".