{"id":"W3213445823","doi":"10.1364/dh.2021.dth4f.3","title":"Ongoing challenges with Edge Machine Learning for Radiation Instrumentation","year":2021,"lang":"en","type":"article","venue":"OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Instrumentation (computer programming); Computer science; Detector; Enhanced Data Rates for GSM Evolution; Particle detector; Embedded system; Artificial intelligence; Operating system; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001546304,0.0002474099,0.0002792003,0.0001233997,0.0004236067,0.0002961776,0.00009447222,0.00005980921,0.000096829],"category_scores_gemma":[0.00002269397,0.0002452911,0.00005475572,0.0001935669,0.00009574478,0.0001891197,0.00006235576,0.0002764494,0.00001134837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003999895,"about_ca_system_score_gemma":0.0000602652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001140847,"about_ca_topic_score_gemma":0.00001277271,"domain_scores_codex":[0.9987373,0.00003485831,0.0002699081,0.0004759154,0.0001804875,0.0003015793],"domain_scores_gemma":[0.9992151,0.000134752,0.0002148029,0.0002248648,0.0001301099,0.00008034764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005674564,0.00007930296,0.01808101,0.00007746157,0.000159942,0.00000368507,0.0006813619,0.004082016,0.003762042,0.01467622,0.0001637478,0.9581764],"study_design_scores_gemma":[0.01283857,0.0003133156,0.005693077,0.0003766942,0.0005418825,0.00005307312,0.03024391,0.5478609,0.2502219,0.003269527,0.1459029,0.00268415],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9365171,0.003411548,0.03290021,0.003548454,0.001086072,0.001112411,0.0001033793,0.0004840251,0.0208368],"genre_scores_gemma":[0.9933618,0.0004124438,0.005239995,0.0000668689,0.0002100743,0.0001191066,0.00009853942,0.00003867585,0.0004524416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9554923,"threshold_uncertainty_score":0.9999999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009806747520604097,"score_gpt":0.2296251976970736,"score_spread":0.2198184501764695,"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."}}