ORNAC 23rd National and IFPN International Conference: International alliance for perioperative best practice: The Ottawa convention centre, Ottawa, Ontario, Canada, 21-25 April 2013
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It was a privilege to attend this year’s joint Operating Room Nurses Association of Canada (ORNAC) and International Federation of Perioperative Nurses (IFPN) Conference hosted in Ottawa, Canada on 21–25 April 2013 to present on my research findings via my paper: “Perioperative Nurses: Finding Meaning from their Experiences in Multi-Organ Procurement Surgery”. After presenting my preliminary PhD research findings at the previous ORNAC Conference, I vowed to return and present my final PhD findings at a future ORNAC Conference. I submitted my abstract; however, little did I know that I would be expecting my fourth child and racing to complete my PhD before the baby’s arrival. When I received notification my paper had been accepted this caused some dilemmas as to how I was going to get there, leave a small baby and fulfil my obligation to present my PhD findings. The solution was a quick visit, several interconnecting flights to get to the conference, stay for a couple of days, present my paper and return home as quickly as possible.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it