{"id":"W4289782747","doi":"","title":"3D Digital SiPM and Smart Silicon Interposer for nEXO","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"3D IC and TSV technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Silicon photomultiplier; Silicon; Optoelectronics; Interposer; Computer science; Materials science; Detector; Telecommunications; Nanotechnology; Etching (microfabrication); Layer (electronics)","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":[0.0007651272,0.0002780744,0.0002879341,0.0001343359,0.0001060522,0.0003380077,0.0006428813,0.00031925,0.00002931327],"category_scores_gemma":[0.0007100778,0.0002556765,0.0001173316,0.0000858128,0.0001983647,0.0001661417,0.0006984586,0.0003298532,0.00002378366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007002272,"about_ca_system_score_gemma":0.00004102665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003274259,"about_ca_topic_score_gemma":0.0001151532,"domain_scores_codex":[0.9986786,0.0001779311,0.0003056279,0.0004253998,0.0001279038,0.0002845206],"domain_scores_gemma":[0.9974799,0.0007637326,0.0001096013,0.001133263,0.0004283405,0.00008518308],"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":[0.00002424016,0.0002444358,0.005197535,0.001035617,0.0003648904,0.000005086305,0.004941931,0.00008191419,0.008151234,0.08560829,0.008403175,0.8859416],"study_design_scores_gemma":[0.003357456,0.000003968816,0.008114844,0.01063774,0.0002213117,0.00005104101,0.000608638,0.1361407,0.3127671,0.1418731,0.3826126,0.003611458],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2955013,0.003286251,0.5838558,0.006046913,0.0006525685,0.001042216,0.0004343778,0.002483406,0.1066972],"genre_scores_gemma":[0.9854711,0.0005148585,0.009581783,0.00002161923,0.00002098058,0.0001248288,0.0001666757,0.00005968404,0.004038428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8823302,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008732218100106,"score_gpt":0.2024333131863392,"score_spread":0.1923459910053382,"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."}}