{"id":"W1993582662","doi":"10.1049/el:20031198","title":"Digital camera zooming on colour filter array","year":2003,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer vision; Zoom; Artificial intelligence; Computer science; Noise (video); Filter (signal processing); Enhanced Data Rates for GSM Evolution; Color filter array; Adaptive filter; Digital filter; Image sensor; Digital camera; Computer graphics (images); Image (mathematics); Engineering; Color gel; Algorithm","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":[0.0001685826,0.0003071978,0.0002325606,0.0004776146,0.0002028705,0.0002520204,0.000454674,0.0002146924,0.004573031],"category_scores_gemma":[0.0004018384,0.000189599,0.0001795092,0.0004151919,0.0001765339,0.0004714188,0.0003045186,0.0002720667,0.001014058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000290011,"about_ca_system_score_gemma":0.0002118773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007088637,"about_ca_topic_score_gemma":0.001499089,"domain_scores_codex":[0.9998628,0.00001394141,0.000004069051,0.00002717541,0.00008020487,0.00001185278],"domain_scores_gemma":[0.9997742,0.00006374641,0.000018449,0.00003923416,0.00008569782,0.00001871806],"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":[0.0002038393,0.0000268595,0.0002728364,0.0001557901,0.00001717515,0.00009952182,0.00009450768,0.004520351,0.6564813,0.007069818,0.002291978,0.3287661],"study_design_scores_gemma":[0.00006461929,0.0003617152,0.003610513,0.00005395654,0.00005033659,0.001218345,0.00005166256,0.2496423,0.7037274,0.004745524,0.03641109,0.00006258817],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04636469,0.000430783,0.9439717,0.00007953139,0.0001044252,0.00009312084,0.00008421694,0.002398934,0.006472628],"genre_scores_gemma":[0.1791405,0.0005659974,0.8102567,0.0001015016,0.00005307147,0.00007990743,0.0001416623,0.0001954064,0.009465309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004573031,"threshold_uncertainty_score":0.01529825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006350863864631526,"score_gpt":0.2132619072278155,"score_spread":0.2069110433631839,"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."}}