Bibliographic record
Abstract
OBACIS is a tri-platform outcome-based assessment and continues improvement system. The system is composed of three integrated platforms/applications: A Win app, an Excel app, and a Web-app. OBACIS I demonstrated the tri-platform integrated framework in addition to a data-driven course improvement system.OBACIS II introduced the parsing engine and the autogenerated course information sheets (CIS), demonstrated how 80% of CIS data collection time could be saved, and demonstrated how to make compiling CIS data an ongoing continuous improvement activity. OBACIS III introduced the Excel Application that collects the data missed by theparsing engine of OBACIS II and introduced thesimultaneous grade and accreditation reporting system.OBACIS III demonstrated how the time required to do the two tasks could be cut down by almost 50%. OBACIS IV introduced the closed loop teaching and learningframework. OBACIS V prepares the accreditation reportsthat that meets the CEAB new criteria guided and definedby the CEAB questionnaire, tables, and exhibits
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".