{"id":"W4229626389","doi":"10.1149/ma2008-02/27/2029","title":"CMOS Camera-on-Chip Image Sensor for Biomedical Applications","year":2008,"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 Medical Centre; University of Toronto; McMaster University","funders":"","keywords":"Image sensor; CMOS; Chip; Computer science; CMOS sensor; Artificial intelligence; Embedded system; Computer vision; Computer hardware; Electronic engineering; Engineering; Telecommunications","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":[0.0002347217,0.0005760122,0.0005720527,0.0003578325,0.0002876431,0.0005060693,0.001173388,0.001181699,0.03346656],"category_scores_gemma":[0.0005268857,0.0003112888,0.0002719811,0.0004116779,0.0001875061,0.0006770168,0.0002781017,0.000851465,0.009103721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005956051,"about_ca_system_score_gemma":0.0007229958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041683,"about_ca_topic_score_gemma":0.002914657,"domain_scores_codex":[0.9996756,0.00002217465,0.000009710032,0.00006549026,0.0001923734,0.00003471544],"domain_scores_gemma":[0.9997711,0.00003311001,0.00001412925,0.00002091521,0.0001327476,0.00002800814],"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":[0.0003008412,0.0001009222,0.0002840773,0.000704261,0.00003886975,0.0001190469,0.00002001996,0.0002566309,0.8939086,0.001965951,0.03404335,0.06825744],"study_design_scores_gemma":[0.0001276434,0.001015632,0.003715668,0.0000781775,0.0001213486,0.001078577,0.00003282304,0.01311295,0.8055213,0.0005533761,0.1745974,0.00004510306],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1376376,0.03392185,0.6412962,0.006318295,0.008271267,0.002932146,0.0119837,0.01221041,0.1454285],"genre_scores_gemma":[0.3936591,0.01397646,0.3712777,0.003799388,0.00101885,0.001295082,0.007899434,0.0006150485,0.206459],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03346656,"threshold_uncertainty_score":0.1119568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389047996302977,"score_gpt":0.238355033316035,"score_spread":0.2244645533530052,"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."}}