{"id":"W3184016808","doi":"10.1038/s41467-021-24725-1","title":"Spin defects in hBN as promising temperature, pressure and magnetic field quantum sensors","year":2021,"lang":"en","type":"article","venue":"Nature Communications","topic":"Diamond and Carbon-based Materials Research","field":"Materials Science","cited_by":286,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Centre of Excellence for Electromaterials Science, Australian Research Council; Deutsche Forschungsgemeinschaft; Asian Office of Aerospace Research and Development; Australian Research Council; Alexander von Humboldt-Stiftung","keywords":"Condensed matter physics; Magnetic field; Spin (aerodynamics); Materials science; Boron nitride; Heterojunction; Photoluminescence; Hexagonal boron nitride; Spin states; Boron; Ground state; Optoelectronics; Nanotechnology; Physics; Atomic physics; Graphene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003883149,0.0001251625,0.0001850313,0.00008413297,0.0001934262,0.0002638182,0.0005297144,0.0002886129,0.0002395549],"category_scores_gemma":[0.0008300635,0.0001174167,0.00003303619,0.0003041003,0.0001060725,0.0001214445,0.000428776,0.0006593345,0.00003321312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000164784,"about_ca_system_score_gemma":0.0001842265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001095766,"about_ca_topic_score_gemma":0.000406591,"domain_scores_codex":[0.9986339,0.0004108667,0.0002020374,0.0002794669,0.0002131256,0.0002606471],"domain_scores_gemma":[0.998199,0.0004006765,0.00004393272,0.001126851,0.0001427828,0.00008674874],"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":[0.00002114093,0.0001046926,0.0008136359,0.00006720075,0.00000444373,0.00002188334,0.0001857454,0.00001332232,0.989681,0.00786315,0.000912719,0.0003110625],"study_design_scores_gemma":[0.0007154835,0.0001601353,0.008454638,0.0002808539,0.00004432127,0.00005520149,0.000387162,0.000597441,0.9633312,0.002654374,0.02296072,0.0003584689],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647139,0.02802186,5.5158e-7,0.003057968,0.0001826651,0.0002252316,0.00002418095,0.00004920885,0.003724392],"genre_scores_gemma":[0.9969893,0.0009775819,0.000959581,0.0005196255,0.00003817912,0.00002969762,0.00002954746,0.0000156784,0.0004408243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03227535,"threshold_uncertainty_score":0.4788112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475983576772652,"score_gpt":0.313296236801799,"score_spread":0.2985364010340724,"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."}}