{"id":"W2905768928","doi":"","title":"Text Enhancement in Projected Imagery","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Thresholding; Filter (signal processing); Artificial intelligence; Projection (relational algebra); Range (aeronautics); Class (philosophy); Quality (philosophy); Visualization; Image (mathematics); Pattern recognition (psychology); Computer vision; Algorithm; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002747579,0.0006842835,0.000347578,0.0005666874,0.0001528386,0.0005852713,0.0003476932,0.0003625645,0.002813794],"category_scores_gemma":[0.001094079,0.0002619777,0.0004462322,0.0003690182,0.0004100685,0.000979424,0.0006360451,0.0005206584,0.0008946088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001380092,"about_ca_system_score_gemma":0.0001366863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003264296,"about_ca_topic_score_gemma":0.0005221763,"domain_scores_codex":[0.9998048,0.00003102571,0.000008728766,0.00004114177,0.00009234819,0.00002198404],"domain_scores_gemma":[0.9995967,0.0001290381,0.00005524625,0.00007604282,0.0001134737,0.00002958004],"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":[0.0006287011,0.00005849298,0.0006265409,0.0004523702,0.00004800601,0.0004094236,0.0001681132,0.01423156,0.7141045,0.002283948,0.001533028,0.2654554],"study_design_scores_gemma":[0.00006150922,0.0006526056,0.007913653,0.00006769578,0.00009910062,0.00256081,0.0001361031,0.2309527,0.7426771,0.00305624,0.01177148,0.00005100981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1945425,0.001663183,0.7946007,0.0002295741,0.0001315301,0.0001209631,0.0001781576,0.002018548,0.006514776],"genre_scores_gemma":[0.5495819,0.001905921,0.4363154,0.0002319135,0.0001587268,0.00006501082,0.0003908689,0.0003630995,0.01098712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002813794,"threshold_uncertainty_score":0.009413064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100820671520164,"score_gpt":0.3154719451779164,"score_spread":0.3044637384627148,"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."}}