{"id":"W3067687984","doi":"10.1103/physrevd.103.075002","title":"Silicon carbide detectors for sub-GeV dark matter","year":2021,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Dark Matter and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Laboratory Directed Research and Development; Office of Science; Israeli Centers for Research Excellence; Azrieli Foundation; Israel Science Foundation; United States-Israel Binational Science Foundation; Alfred P. Sloan Foundation; Basic Energy Sciences; National Energy Research Scientific Computing Center; German-Israeli Foundation for Scientific Research and Development; Fermilab; High Energy Physics; U.S. Department of Energy","keywords":"Dark matter; Silicon carbide; Diamond; Silicon; Detector; Absorption (acoustics); Scattering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002895668,0.0007271808,0.001964026,0.00003489558,0.0001799698,0.00009170469,0.0006240859,0.00002124728,0.0001531467],"category_scores_gemma":[0.000111628,0.0006161861,0.001657578,0.0006203448,0.0001134858,0.0002890835,0.0002831605,0.0005066373,0.001669236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007850092,"about_ca_system_score_gemma":0.0001742238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002762238,"about_ca_topic_score_gemma":0.000001693466,"domain_scores_codex":[0.996326,0.0002856318,0.0008229149,0.001093866,0.0005514083,0.0009201934],"domain_scores_gemma":[0.997154,0.0004909288,0.0003510936,0.001264248,0.0002965583,0.0004431923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004720202,0.003335853,0.0193881,0.02424134,0.0008338995,0.0000166399,0.0001762613,0.000006770599,0.2113882,0.02644828,0.5438196,0.1702978],"study_design_scores_gemma":[0.001547104,0.0002851849,0.006104843,0.01576226,0.002452824,0.000007901448,0.00004078179,0.0002136626,0.05882329,0.6821847,0.2298886,0.002688827],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8644952,0.04323235,0.0005016786,0.005053538,0.00047399,0.003096614,0.0004848434,0.0001613142,0.08250053],"genre_scores_gemma":[0.9641421,0.006784037,0.0001239899,0.02507741,0.001729205,0.001249576,0.0003918661,0.0001447703,0.0003570888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6557364,"threshold_uncertainty_score":0.999629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223089812540847,"score_gpt":0.3667669098882725,"score_spread":0.3545360117628641,"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."}}