{"id":"W2104568678","doi":"10.1109/cicc.2007.4405854","title":"A CMOS Image Sensor for DNA Microarrays","year":2007,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University Health Network","keywords":"CMOS; Photomultiplier; Image sensor; Pixel; Scanner; Noise (video); CMOS sensor; Chip; DNA microarray; Computer science; Optoelectronics; Physics; Artificial intelligence; Image (mathematics); Optics; Chemistry; Detector; Gene expression; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003991606,0.0007572034,0.0005906555,0.0006882279,0.0005612136,0.0005399174,0.001659551,0.001170349,0.005978181],"category_scores_gemma":[0.0008141156,0.0004605001,0.0004164292,0.0008401301,0.0003753087,0.0008319712,0.0005175504,0.001176629,0.004424335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008378121,"about_ca_system_score_gemma":0.00079548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006145683,"about_ca_topic_score_gemma":0.001149785,"domain_scores_codex":[0.9989303,0.00007973238,0.00004373977,0.0001809626,0.0007103038,0.0000550032],"domain_scores_gemma":[0.9997461,0.00005267116,0.00002403097,0.00002911328,0.0001154063,0.00003258689],"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":[0.00006706456,0.00004372197,0.0001930584,0.0004844672,0.00001669235,0.0001324859,0.00004383378,0.0004720928,0.9200727,0.004633549,0.0114772,0.06236331],"study_design_scores_gemma":[0.00003293648,0.0001846545,0.0005699887,0.0000267263,0.00003149866,0.001232912,0.00002032846,0.008624502,0.8542424,0.001140374,0.1338527,0.00004112818],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02374123,0.008942267,0.9243362,0.001538565,0.001809222,0.000821469,0.002599419,0.01089091,0.02532073],"genre_scores_gemma":[0.078386,0.003792631,0.8846004,0.001211825,0.0002508801,0.0008952406,0.002270514,0.0003182551,0.02827433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005978181,"threshold_uncertainty_score":0.01999897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006113259212427061,"score_gpt":0.2177130851669298,"score_spread":0.2115998259545027,"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."}}