Bibliographic record
Abstract
KEYWORDS:Wisdom, Person-centred care, Death and dying 'd like to see princess of the night."New-onset confusion, probably a UTI.I glanced at the man sitting next to me, scrunched up in his wheelchair.He was fresh from the shower this morning, wrapped in towels and two gowns.His hands folded neatly on his lap.They were not pulling on his catheter."Maybe later, Norm."I smiled at him, switching his GCS assessment from a 15 down to a 14.Hopefully they'll start him on some macrobid."I'll get you some pain meds and we can do your dressing in a bit."He asked to see princess of the night again when I walked in to change his vac dressing.Another task on my to-do list for the day.Beth pulled out her third IV of the day, Steve started on a heparin drip, at least Ron is sleeping now -he was trying to throw a bedpan at me two hours ago.Please don't be aggressively confused, just be sweetly confused.I thought to myself as I peeled Norm's dressing back.At least I'll have 30 minutes of peace and quiet while I do this, away from all the chaos outside. "I
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.109 | 0.037 |
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".