{"id":"W3089301772","doi":"10.1073/pnas.2012980117","title":"Tunable layered-magnetism–assisted magneto-Raman effect in a two-dimensional magnet CrI <sub>3</sub>","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"2D Materials and Applications","field":"Materials Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Army Research Office; Fundamental Research Funds for the Central Universities; U.S. Army; Renmin University of China; National Natural Science Foundation of China; Division of Materials Research; Canada First Research Excellence Fund; National Science Foundation","keywords":"Magnetism; Raman spectroscopy; Condensed matter physics; Multiplet; Magneto optical; Antiferromagnetism; Phonon; Magnet; Raman scattering; Polarization (electrochemistry); Magnetic field; Coupling (piping); Materials science; Physics; Chemistry; Optics; Spectral line; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001537842,0.0001603564,0.000282912,0.0001163986,0.0002066687,0.0000816426,0.0009525635,0.00007166982,0.0001788458],"category_scores_gemma":[0.0004301098,0.0001132431,0.00007382796,0.0009406397,0.0006566847,0.0004766406,0.0003034715,0.0001433152,0.00003224417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003255744,"about_ca_system_score_gemma":0.00005359194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003095163,"about_ca_topic_score_gemma":5.103951e-7,"domain_scores_codex":[0.9976004,0.00002522738,0.0005172811,0.0004457213,0.001131709,0.0002797013],"domain_scores_gemma":[0.9991408,0.0001596943,0.0004154283,0.00001598837,0.0001833864,0.00008471731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003726595,0.00004700611,0.0006965651,0.00009182274,0.000002138261,3.003354e-8,0.00007250989,0.0004047648,0.9884872,0.008053572,0.001816137,0.000291023],"study_design_scores_gemma":[0.000424833,0.0001352098,0.02665685,0.00006949991,0.00001095849,0.000005893226,0.00003235452,0.00155237,0.9606344,0.01021723,0.0001341937,0.0001262303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903646,0.00009961776,7.842798e-7,0.006789161,0.00003433411,0.0003830383,0.00005472458,0.00003218509,0.002241585],"genre_scores_gemma":[0.997412,0.000006704018,0.001487125,0.0008837635,0.0001113949,0.00005945526,5.737422e-7,0.000007968244,0.00003101059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02785278,"threshold_uncertainty_score":0.461792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0297252381832733,"score_gpt":0.2910534487513436,"score_spread":0.2613282105680703,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}