{"id":"W2145784838","doi":"","title":"CMOS photodetectors and imaging systems for biomedical applications","year":2009,"lang":"en","type":"article","venue":"Computers and Devices for Communication, 2009. CODEC 2009. 4th International Conference on","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Photodetector; CMOS; Sensitivity (control systems); Image sensor; Computer science; Process (computing); Medical imaging; Electronic engineering; Materials science; Optoelectronics; Engineering; Artificial intelligence","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":[0.0001846601,0.0002112917,0.0002176906,0.0001735431,0.0002320834,0.0002904807,0.0004637914,0.00006415892,0.000006072735],"category_scores_gemma":[0.00001749436,0.0002127727,0.00005488686,0.0001004225,0.0001030194,0.0001858824,0.00004406127,0.0001326764,0.000003415799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004743783,"about_ca_system_score_gemma":0.00002420599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000284337,"about_ca_topic_score_gemma":0.00001469552,"domain_scores_codex":[0.9989654,0.00002267832,0.0003516531,0.0002777716,0.0001648823,0.0002175443],"domain_scores_gemma":[0.9989688,0.0002139683,0.0000980643,0.0003589778,0.000239232,0.0001208975],"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":[0.0002522014,0.0005303241,0.002254379,0.0005351102,0.0004387877,0.000002881559,0.001964583,0.006598592,0.004209507,0.2870975,0.06037629,0.6357398],"study_design_scores_gemma":[0.0007783695,0.00008074105,0.001166643,0.0001931589,0.00002580406,0.00001833198,0.0001947883,0.8165314,0.00007635052,0.003324187,0.1773192,0.0002909545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04137564,0.01436536,0.9182049,0.008902856,0.001790351,0.003474683,0.0009820005,0.0009991358,0.009905072],"genre_scores_gemma":[0.9897431,0.001372581,0.00764636,0.0004826323,0.0001441165,0.0001870575,0.0002829381,0.00002333583,0.0001178872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9483675,"threshold_uncertainty_score":0.8676618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115346224386146,"score_gpt":0.2767854944234396,"score_spread":0.2556320321795781,"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."}}