Bibliographic record
Abstract
Morgan Kendrick, Vice President of Business Development and Patient Safety at BuyPro Health group purchasing organisation (GPO), contemplated his options regarding the IT infrastructure project he hoped to champion as he took his new position in January of 2017. BuyPro was a prominent Canadian healthcare GPO. Kendrick hoped to leverage BuyPro’s prominent industry position to promote adoption of global standards for procurement and service delivery purposes. In order for BuyPro to adopt global standards and use them as effectively as Kendrick wished, the company would need to invest substantially in upgrading internal systems to make them standards-ready. However, investment in the required systems upgrades would not directly facilitate negotiating for lower unit pricing on supplies purchased by member organisations. As he considered the future needs of the company and its industry, Morgan considered how best to promote his vision and build support for the necessary precursor investments.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.018 | 0.012 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".