{"id":"W2737893188","doi":"10.1149/ma2010-01/19/1055","title":"High-Speed Ultra-Sensitive Biomedical CMOS Imagers","year":2010,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"CMOS; Computer science; Optoelectronics; Materials science","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":[0.0003398839,0.0002365031,0.0002210665,0.0001067471,0.0001012815,0.00008560362,0.0001585169,0.000154852,0.00006365906],"category_scores_gemma":[0.0004075297,0.0002399808,0.00007646153,0.000180825,0.0001463023,0.0001170621,0.00001489723,0.000739295,0.000466987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003131037,"about_ca_system_score_gemma":0.00002401912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001597847,"about_ca_topic_score_gemma":0.00001349964,"domain_scores_codex":[0.9986045,0.00001723275,0.0003286825,0.0002616505,0.0002931494,0.000494764],"domain_scores_gemma":[0.9991516,0.0002197325,0.00005765662,0.000270456,0.00006057822,0.0002400049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004703163,0.00002957206,0.0001108601,0.00002403642,0.00002873255,0.0001415919,0.000407694,0.01638658,0.9781763,0.000009803913,0.003165864,0.001514292],"study_design_scores_gemma":[0.0005087254,0.00001845788,0.01022876,0.00008688432,0.00002904757,0.000176437,0.0002335245,0.004002212,0.975952,0.00008873719,0.008201861,0.000473397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9212111,0.00001988333,0.0000134345,0.0002980704,0.002155636,0.00008637339,0.0000150635,0.0007996908,0.07540076],"genre_scores_gemma":[0.9958976,0.000008863179,0.00303453,0.00008853229,0.0007072093,0.000001928203,0.00002279961,0.00006612454,0.000172427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07522833,"threshold_uncertainty_score":0.9786131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005654767136969003,"score_gpt":0.2086874691524939,"score_spread":0.2030327020155249,"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."}}