{"id":"W4285585796","doi":"10.1117/12.2642961","title":"Machine learning techniques to separate the cosmic from the telluric","year":2022,"lang":"en","type":"article","venue":"Space Telescopes and Instrumentation 2022: Optical, Infrared, and Millimeter Wave","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"COSMIC cancer database; Computer science; Cosmic ray; Astronomy; Physics","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":[0.0003711142,0.0001769579,0.0001576127,0.00004498448,0.001021106,0.0003098717,0.0003616846,0.00003657618,0.0001810613],"category_scores_gemma":[0.00005588311,0.0001145311,0.00004199283,0.0003241907,0.0001235172,0.0001853752,0.0008651194,0.0003652821,0.000007310364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002747665,"about_ca_system_score_gemma":0.00002820584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001510362,"about_ca_topic_score_gemma":0.00001073582,"domain_scores_codex":[0.9987345,0.0001508872,0.0002141416,0.0004039299,0.0002374312,0.000259149],"domain_scores_gemma":[0.9992564,0.0002186094,0.00008833346,0.0003060457,0.00003981849,0.00009081027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002824246,0.0002431783,0.007324161,0.00009484896,0.0004078475,0.00009351265,0.03222921,0.00121701,0.07710902,0.03850959,0.02979964,0.8126895],"study_design_scores_gemma":[0.0007756781,0.0008613981,0.002770753,0.00004682033,0.00006313639,0.0001484231,0.008377672,0.02191625,0.05035223,0.01199923,0.9020508,0.0006376167],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8815776,0.00331568,0.04695931,0.04454347,0.0005231025,0.001556703,0.0001113867,0.0003385213,0.02107424],"genre_scores_gemma":[0.9537259,0.0008829257,0.03491137,0.005652348,0.00009567445,0.0001855552,0.00006359093,0.00001038388,0.004472294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8722512,"threshold_uncertainty_score":0.7853624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227051130576996,"score_gpt":0.221798945833769,"score_spread":0.2095284345279991,"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."}}