Bibliographic record
Abstract
Abstract This article describes how the author created an academic website in reproductive medicine, and presents data on visitor profiles. The website provides access to interactive lectures, computer-generated tests, quizzes, searchable databases, and a bulletin board for approved users. The website is international in scope, collaborative, asynchronous in delivery, flexible, and responsive to learner needs. Visitors from industrialized countries accessed the lessons on polycystic ovary syndrome, amenorrhea, and infertility. In 2004, the total number of unique visitors was 21,269. Introduction In recent years, increasing numbers of medical institutions in the United States and abroad have incorporated innovative methods of teaching and research using the Internet technologies (Barzansky et al. 2000; Jenkins, 2002; Zondervan et al. 2002). The Association of Professors of Gynecology and Obstetrics (APGO) website reveals several medical centers in the United States and Canada have also established departmental websites (APGO, 2005). The links provide information on what other institutions are doing with regard to medical education programs, residencies and fellowships, departments and faculty, patient care and research. Besides healthcare professionals, many infertile couples are actively using the Internet for their fertility problems (Weissman et al. 2000; Epstein et al. 2002; Haagen et al. 2003). However, posting of information on the Internet does not always undergo peer reviews or need some standard for publication. The use of standardized curriculum and innovative techniques for providing education are important steps for graduate training of future doctors in reproductive medicine (Soules, 1994; Davis et al. 1995; Jenkins, 1999; Alvero et al. 2004). The World Wide Web provides a delivery system for transferring information to many users without the barriers of time and geography (Chu & Chan, 1998). Developing web-based learning represents an evolution that needs experienced website designers, surveys of the targeted audience, focus groups, and analysis of server data or a combination of these methods (Letterie et al. 1994, 1996; Jenkins et al. 2001). Web-based learning may be suitable setting for women's health issues because of the multidisciplinary nature and need for vertical integration throughout medical school curriculums. According to a recent study, the web-based instruction resolved barriers associated with limited curriculum time and faculty availability, provided an accessible and standard curriculum, and met the needs of adult learners in a medicine clerkship (Zebrack et al. 2005). More studies in defined clinical settings are needed to realize the full potentials of web-based learning for women's health education. Websites designed at academic institutions and departments must present authentic content, be consistent in navigation, use simple graphics, and highlight ease of maintenance (Singh, 2002). Towards this end, the department of obstetrics and gynecology at the Louisiana State Health Sciences Center in Shreveport launched the first academic website in September 1997. This article describes how the author created an academic website in reproductive medicine, and presents data on visitor profiles to show how they used the website in recent years. Methods The departmental server (PowerEdge 2300, Dell Computer Corporation, Round Rock, TX) runs under Windows 2000 operating system (Microsoft Corporation, Redmond, WA). Ancillary units installed were an automated tape backup, uninterruptible power supply, an antivirus software program, and a redundant array of independent disks to provide safety measures against unexpected system failures. The design for the website followed guidelines proposed by the Journal of American Medical Association (JAMA) core standards for publications (Silberg et al. 1997). The individual pages were created using a software that creates web pages with hypertext markup language (NetObjects Fusion, Website Pros, Inc. …
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.106 | 0.036 |
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".