Disentangling superconducting and magnetic orders in NaFe1-xNixAs using muon spin rotation
Bibliographic record
Abstract
Agradecimentos: The mu SR experiments were performed at TRIUMF in Vancouver, Canada and at the Swiss Muon Source (S mu S) at Paul Scherrer Insitute (PSI) in Villigen, Switzerland. The authors sincerely thank the TRIUMF Center for Material and Molecular Science staff and the PSI Bulk mu SR Group for invaluable technical support with mu SR experiments. Work at the Department of Physics of Columbia University is supported by US NSF DMR-1436095 (DMREF) and NSF DMR-1610633. Z.G. gratefully acknowledges the financial support by the Swiss National Science Foundation (SNF fellowships P2ZHP2-161980 and P300P2-177832). Work at Columbia, TRIUMF, PSI, and IOP-Beijing has been supported by the REIMEI project funding from the Japan Atomic Energy Agency, and by the support from the Friends of Tokyo University Inc (FUTI). E.M. is supported by CNPq (Grant No. 304311/2010-3). P.B. acknowledges computing resources provided by STFC Scientific Computing Department's SCARF cluster. R.D.R. acknowledges funding by H2020 Research Infrastructures under Grant Agreement No. 654000. This work was supported by the computational node hours granted from the Swiss National Supercomputing Centre (CSCS) under project ID sm07. R.M.F. is supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award No. DE-SC0012336. C.D.C. acknowledges financial support by the National Natural Science Foundation of China Grant No. 51471135, the National Key Research and Development Program of China under Contract No. 2016YFB1100101, and Shaanxi International Cooperation Program. Works at IOPCAS are supported by NSF and MOST of China through Research Projects as well as by CAS External Cooperation Program of BIC (112111KYS820150017). The Ni-doped NaFeAs single crystal growth efforts at Rice University are supported by DOE, BES, DE-SC0012311, and by the Robert A. Welch Foundation Grant No. C-1839 (P.D.). The present work is a part of the Ph.D. thesis of S.C.C. submitted to and defended at Columbia University in August 2017
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".