{"id":"W2117435310","doi":"10.1109/iscas.2007.378030","title":"A CMOS Contact Imager for Cell Detection in Bio-Sensing Applications","year":2007,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"CMOS; Biosensor; Reset (finance); Sensitivity (control systems); Computer science; Pixel; Noise (video); CMOS sensor; Image sensor; Electronic engineering; Computer hardware; Nanotechnology; Materials science; Engineering; Artificial intelligence; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003461356,0.000503217,0.0005763804,0.0004775729,0.0005094283,0.0007510125,0.001362556,0.0008666327,0.009873089],"category_scores_gemma":[0.0007123754,0.0003032225,0.0003360308,0.0006347558,0.0003648823,0.0009142059,0.0004781783,0.0008269917,0.005469412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006162514,"about_ca_system_score_gemma":0.0005788874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007779195,"about_ca_topic_score_gemma":0.001395708,"domain_scores_codex":[0.9993394,0.00005448729,0.00003375986,0.0001394332,0.0003970049,0.0000359364],"domain_scores_gemma":[0.9996618,0.0001134222,0.00003180487,0.0000568413,0.0001043547,0.00003177231],"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":[0.0001175001,0.0000373119,0.0002088676,0.0002955573,0.00001164125,0.0002149042,0.00007308262,0.0002798846,0.9132046,0.005925039,0.006876397,0.07275528],"study_design_scores_gemma":[0.00004468575,0.000408965,0.001558228,0.00003366014,0.00005278707,0.002865307,0.00003508244,0.01303588,0.859682,0.001309015,0.1209243,0.00005001336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02707937,0.004946047,0.9255639,0.0007262966,0.0007000258,0.0004994387,0.001346398,0.009609744,0.02952867],"genre_scores_gemma":[0.155121,0.002778931,0.8067013,0.0009057922,0.0002803884,0.000394707,0.0009827678,0.0004710738,0.03236408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009873089,"threshold_uncertainty_score":0.03302878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005149377024149224,"score_gpt":0.2132373016798464,"score_spread":0.2080879246556972,"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."}}