{"id":"W2071289785","doi":"10.2316/journal.206.2014.4.206-4086","title":"A SPARSE BASED RAIN REMOVAL ALGORITHM FOR IMAGE SEQUENCES","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Image (mathematics); Computer science; Artificial intelligence; Algorithm; Pattern recognition (psychology); Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007515624,0.00006348456,0.0001020852,0.0001670318,0.00003621545,0.0002176051,0.0003817402,0.00003023786,0.000007123612],"category_scores_gemma":[0.0002675736,0.00005370061,0.00005287064,0.00006060615,0.00004042896,0.0005734722,0.00003492634,0.000062353,0.000001421687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003787846,"about_ca_system_score_gemma":0.00006064716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000025961,"about_ca_topic_score_gemma":3.699476e-7,"domain_scores_codex":[0.9990392,0.00005188626,0.0003302927,0.0000937454,0.0004099125,0.00007495048],"domain_scores_gemma":[0.9988136,0.0001830491,0.0003432288,0.00006965346,0.0005287153,0.00006181101],"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":[0.00000460096,0.00004388153,0.00001643255,0.000008833968,0.00002551137,0.00002223564,0.00008922954,0.0008307023,0.005506948,0.008032698,0.0008687553,0.9845502],"study_design_scores_gemma":[0.0005480799,0.0001244066,0.000181446,0.00006027726,0.000006686933,0.0001488729,0.000009249782,0.9764096,0.01202178,0.009858957,0.0005677645,0.00006287741],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004172822,0.00001937875,0.9950043,0.003874573,0.0004948102,0.00007100779,0.000002522874,0.00003830307,0.00007785352],"genre_scores_gemma":[0.02393469,0.00001398542,0.9752138,0.0006196831,0.0001805767,0.000002436187,0.000004704114,0.000003963477,0.00002621919],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9844873,"threshold_uncertainty_score":0.2189847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540249960629796,"score_gpt":0.3003890235021301,"score_spread":0.2849865238958322,"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."}}