{"id":"W4417471442","doi":"10.1109/nss/mic/rtsd57106.2025.11286980","title":"A 3D Low-Power Photon-to-Digital Converter - Radiation Detection Applications","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"National Nuclear Security Administration; U.S. Department of Energy","keywords":"Time-to-digital converter; Converters; Instrumentation (computer programming); Full width at half maximum; Nuclear electronics; Neutron; CMOS","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004361669,0.0002892785,0.0002690865,0.0002063113,0.0002630582,0.0002881005,0.0002295167,0.000169212,0.0002495625],"category_scores_gemma":[0.00003862396,0.000297622,0.0001308042,0.0008521706,0.0001561012,0.0003535849,0.0002099873,0.000296168,0.001152277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001802519,"about_ca_system_score_gemma":0.00007912406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002069943,"about_ca_topic_score_gemma":0.000003119696,"domain_scores_codex":[0.9984389,0.00001307207,0.0004062507,0.0005812726,0.0001379814,0.000422549],"domain_scores_gemma":[0.9989184,0.0001316816,0.0000961062,0.0006045277,0.0001475496,0.0001016928],"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":[0.00003894013,0.000246779,0.0004826206,0.00001463926,0.0001167671,3.709256e-7,0.00004326109,0.0001774696,0.00393634,0.04702383,0.0005043257,0.9474146],"study_design_scores_gemma":[0.00207161,0.0003736625,0.001974338,0.0002142018,0.0002000069,0.000001687808,0.001219351,0.06306911,0.2592307,0.1142977,0.5558453,0.001502382],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01799123,0.00004493342,0.9500102,0.001097575,0.0003161347,0.001214785,0.00004101872,0.0003438246,0.02894034],"genre_scores_gemma":[0.9909651,0.000005293995,0.005433904,0.000317583,0.00007466774,0.0001967912,0.00001896234,0.00002221079,0.002965534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9729738,"threshold_uncertainty_score":0.9999476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003310685308621004,"score_gpt":0.2332948342554757,"score_spread":0.2299841489468547,"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."}}