{"id":"W2735982867","doi":"10.1126/sciadv.1700842","title":"Fluorinated h-BN as a magnetic semiconductor","year":2017,"lang":"en","type":"article","venue":"Science Advances","topic":"Graphene research and applications","field":"Materials Science","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Surface modification; Hexagonal boron nitride; Boron nitride; Semiconductor; Magnetic semiconductor; Materials science; Nanotechnology; Boron; Hexagonal crystal system; Oxygen; Nitride; Chemical engineering; Optoelectronics; Chemistry; Crystallography; Organic chemistry; Graphene; Engineering","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005114694,0.00008487106,0.00009035288,0.00008219703,0.001735323,0.0005782067,0.001692919,0.00001728461,0.0006340656],"category_scores_gemma":[0.0005320063,0.00006704017,0.00002492301,0.0002590388,0.002226914,0.001702303,0.000230877,0.00006553885,0.001279351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002607139,"about_ca_system_score_gemma":0.0002262951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001019742,"about_ca_topic_score_gemma":0.0000258638,"domain_scores_codex":[0.9984688,0.00001386267,0.0001120364,0.0004192987,0.0005019965,0.0004840691],"domain_scores_gemma":[0.9987344,0.00002941002,0.00008990008,0.0007829511,0.0001560287,0.0002073017],"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":[0.000003238493,0.00001605389,0.0005147248,0.000003972864,2.103127e-7,0.000002227266,0.00003465957,0.000002685425,0.9841675,0.003895521,0.00006443298,0.01129476],"study_design_scores_gemma":[0.0001240026,0.00008234592,0.006819494,0.00001278259,0.000001699158,0.000007927243,0.00011807,0.00002884365,0.960898,0.01729827,0.01449334,0.0001152111],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853476,0.0006204902,0.00003945366,0.0007371386,0.0002759777,0.0001566667,0.000009540985,0.00006312447,0.01274999],"genre_scores_gemma":[0.9962373,0.00005882236,0.002095708,0.00004826834,0.00005294649,0.00004976495,5.727254e-7,0.000004622869,0.001452043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0232695,"threshold_uncertainty_score":0.9995643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02261751204499972,"score_gpt":0.3521191573517464,"score_spread":0.3295016453067467,"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."}}