Publisher Correction: Probing the strongly driven spin-boson model in a superconducting quantum circuit
Bibliographic record
Abstract
The original PDF and HTML versions of this Article omitted the ORCID ID of the authors L. Magazzù and P. Forn-Díaz. (L. Magazzù: 0000-0002-4377-8387; P. Forn-Diaz: 0000-0003-4365-5157).The original PDF version of this Article contained errors in Eqs. (2), (6), (13), (14), (25), (26). These equations were missing all instances of 'Γ' and 'Δ', which are correctly displayed in the HTML version.Similarly, the inline equation in the third sentence of the caption of Fig. 2 was missing the left hand term 'Ω'.The original HTML version of this Article contained errors in Table 1. The correct version of the sixth row of the first column states 'Figure 2' instead of the original, incorrect 'Figure'. And the correction version of the ninth row of the first column states 'Figure 3' instead of the original, incorrect 'Figure'.This has been corrected in both the PDF and HTML versions of the Article.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.066 | 0.012 |
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".