{"id":"W3111222332","doi":"10.1117/12.2562289","title":"Detector systems engineering for extremely large instruments","year":2020,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Detector; Cutoff; Scientific instrument; Characterization (materials science); Systems design; Control system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442005,0.0005866211,0.0004641172,0.0006652127,0.0007367181,0.001812652,0.001337421,0.00106489,0.01255604],"category_scores_gemma":[0.003411208,0.0005159213,0.0004228306,0.0007583661,0.0005709333,0.001831686,0.001627778,0.002068468,0.007997643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001540918,"about_ca_system_score_gemma":0.001420807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008071632,"about_ca_topic_score_gemma":0.0009682144,"domain_scores_codex":[0.9978858,0.0002292843,0.00008354807,0.0002000458,0.00146045,0.0001409985],"domain_scores_gemma":[0.997888,0.000398358,0.000142893,0.0003738853,0.001100126,0.00009671455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001054232,0.00008818234,0.001487308,0.001107525,0.00007838225,0.0003398645,0.0005483343,0.02172931,0.1419055,0.3617723,0.06153161,0.4093062],"study_design_scores_gemma":[0.00003889751,0.0001917941,0.001083469,0.0001797754,0.00003256611,0.0006158819,0.0001469035,0.05263456,0.05638211,0.06691992,0.8217064,0.0000677749],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003660447,0.002678491,0.9529117,0.001588968,0.0005985443,0.0001887551,0.0002351718,0.002555341,0.0355826],"genre_scores_gemma":[0.1094917,0.004657777,0.8427802,0.0009536784,0.0005223883,0.000584266,0.0008080267,0.001216466,0.03898548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01255604,"threshold_uncertainty_score":0.04200417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01456813208440447,"score_gpt":0.1838597436506086,"score_spread":0.1692916115662041,"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."}}