Mumps Programming Language Family: Mumps Programming Language, Fileman, Mumps Language Syntax, Meditech, Mumps Users, Miis
Bibliographic record
Abstract
Chapters: Mumps Programming Language, Fileman, Mumps Language Syntax, Meditech, Mumps Users, Miis, Profile Scripting Language. Source: Wikipedia. Pages: 38. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Medical Information Technology, Inc., commonly known as MEDITECH, is a Massachusetts-based software and service company selling information systems, which are installed in health care organizations throughout the world. Founded in 1969 by Chairman and CEO A. Neil Pappalardo, MEDITECH has a market share of greater than 22% in the United States and close to 40% in Canada. In 1969, A. Neil Pappalardo began development of MIIS, one of several proprietary implementations of MUMPS, a programming language which at the time had not been standardized. MIIS users and developers later influenced efforts toward MUMPS standardization during the early 1970s; the MUMPS standard was complete by 1974 and approved by 1977. Between 1971 and 1979, Pappalardo developed various other systems, but those associated with integrated health care information remained his primary focus. In 1982, MEDITECH adopted the then-new MAGIC programming language. MAGIC would later become integral to MEDITECH's health care information systems' implementations. In 1994, the company adopted Client/Server, a second software platform to complement MAGIC. While Client/Server utilizes the same MAGIC programming language, it runs differently. MAGIC runs all code on a central server, and clients are in effect dumb terminals. Client/Server executes the code on a users PC, although all code remains centralized. Client server currently supports only Microsoft Windows-based operating systems. MEDITECH unveiled its 6.0 platform in 2006. This platform is MEDITECH's current offering and purports an improved user interface, streamlined workflow...More: http://booksllc.net/?id=715809
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.348 | 0.327 |
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".