Bibliographic record
Abstract
In the NICU with support (continued on p. 3) T he legacy of Heidelise Als lives on and the breadth of the NIDCAP work represented in this issue is a testament to the strength of NIDCAP.Abstracts from the 33rd NIDCAP Trainers Meeting held in Bad Boll, Germany last October come from nine countries, a truly global effect.Profiles from some of the invited presenters and their topics raise so many important issues.Kelly Janssens shows how being political can benefit the work we do, and Karl Heinz Brisch, who unfortunately was unable to be with us shares his important work on outcomes.gretchen Lawhon nicely summarises the meeting in her letter to Heidi highlighting so much of the meeting.I am sure Heidi would love to be kept informed in this way.Regular features of the work of the NIDCAP Training Centres is demonstrated by the team at the Edmonton Training Centre in Canada.We also learn about how developmental care and NIDCAP is expanding throughout New Zealand.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.016 |
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; both teacher heads agree on what is shown here.
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".