{"id":"W1583095495","doi":"10.1007/11499145_26","title":"Joint Spatial-Temporal Color Demosaicking","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Microsoft Research Asia","keywords":"Demosaicing; Artificial intelligence; Computer science; Computer vision; Bayer filter; Joint (building); Color filter array; Color image; Pattern recognition (psychology); Color gel; Image (mathematics); Image processing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002049948,0.0006480807,0.0007486893,0.000913883,0.0003756771,0.0009706864,0.003438449,0.0004016051,0.00005415893],"category_scores_gemma":[0.0001585723,0.0005954033,0.000221316,0.0006479307,0.0006326593,0.0007872772,0.001665072,0.001070944,0.0001213366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004121298,"about_ca_system_score_gemma":0.0007863066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001130081,"about_ca_topic_score_gemma":0.0002646715,"domain_scores_codex":[0.9952346,0.00009905902,0.0007388228,0.001769578,0.001262489,0.0008954395],"domain_scores_gemma":[0.9970847,0.0004490261,0.0003962298,0.001542667,0.0002899185,0.0002374454],"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":[0.000006695212,0.00002166752,0.00002493785,0.0000219867,0.000009150731,0.0002440542,0.0005049856,0.009358295,0.0006036629,0.00576185,0.00004169346,0.983401],"study_design_scores_gemma":[0.0006872157,0.0002916563,0.0002130887,0.0005017949,0.00001591609,0.000264193,1.13974e-7,0.8587748,0.01032206,0.1163575,0.01121998,0.001351713],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00006342441,0.0006180845,0.9899539,0.001299106,0.00237258,0.0003596205,0.000002749293,0.0002460033,0.005084558],"genre_scores_gemma":[0.08263806,0.00002856326,0.9117595,0.003288898,0.001259205,0.0000066267,0.000004608694,0.00004819004,0.0009663513],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9820493,"threshold_uncertainty_score":0.9996498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02982015481288668,"score_gpt":0.2700650970512459,"score_spread":0.2402449422383592,"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."}}