{"id":"W2972717469","doi":"10.36774/jusiti.v7i2.254","title":"Transformasi Citra Biner Menggunakan Metode Thresholding Dan Otsu Thresholding","year":2018,"lang":"id","type":"article","venue":"e-Jurnal JUSITI (Jurnal Sistem Informasi dan Teknologi Informasi)","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Weyerhauser (Canada)","funders":"","keywords":"Thresholding; Grayscale; Artificial intelligence; Pixel; Physics; Computer vision; Computer science; Image (mathematics)","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","sts","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaepi_narrow","scholarly_communication"],"category_scores_codex":[0.003907833,0.002474514,0.002163993,0.002213672,0.003516215,0.005023684,0.007994059,0.001197367,0.00009547506],"category_scores_gemma":[0.0002067882,0.002241236,0.001578455,0.004555195,0.001356275,0.01759067,0.002788639,0.003704848,0.0004017324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001233377,"about_ca_system_score_gemma":0.001313164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002758174,"about_ca_topic_score_gemma":0.00007696849,"domain_scores_codex":[0.9846368,0.0001895302,0.004738483,0.001716533,0.003485891,0.005232772],"domain_scores_gemma":[0.9920193,0.0003164508,0.001800342,0.002540313,0.001250569,0.002073036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001166826,0.001264363,0.01876401,0.002938965,0.003410192,0.002674269,0.1030386,0.01662577,0.01509154,0.1990389,0.01004112,0.6259454],"study_design_scores_gemma":[0.00535888,0.004315306,0.01748416,0.002598855,0.0004455227,0.00759988,0.004131538,0.2139277,0.04122305,0.0002260168,0.6970391,0.005650011],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5232026,0.002555693,0.2099474,0.00314692,0.01708591,0.002295035,0.00003178237,0.002894918,0.2388397],"genre_scores_gemma":[0.9747171,0.001134659,0.01128227,0.003984376,0.004291391,0.00008835433,0.00006837377,0.0001949578,0.004238476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.686998,"threshold_uncertainty_score":0.9987991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364976588363887,"score_gpt":0.24712761880734,"score_spread":0.2234778529237011,"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."}}