{"id":"W4220692292","doi":"10.18280/ria.360103","title":"A Novel Edge Detection Algorithm Based on Outer Totalistic Cellular Automata","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sobel operator; Enhanced Data Rates for GSM Evolution; Cellular automaton; Edge detection; Computer science; Canny edge detector; Image (mathematics); Algorithm; Image gradient; Detector; Key (lock); Image quality; Artificial intelligence; Image processing; Pattern recognition (psychology)","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":[0.0004314432,0.0001955176,0.0001733957,0.000206252,0.0006787063,0.0001655509,0.001149371,0.00004661456,0.0002800633],"category_scores_gemma":[0.00003372784,0.0002168869,0.0001428502,0.0009791924,0.00004997207,0.0001599833,0.0003899577,0.0002930137,0.0005797645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001508313,"about_ca_system_score_gemma":0.00006514466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004633648,"about_ca_topic_score_gemma":0.000003203035,"domain_scores_codex":[0.998107,0.00007496863,0.0003848246,0.0006839916,0.000383175,0.0003660402],"domain_scores_gemma":[0.9982017,0.0001560173,0.0001296093,0.00134073,0.00005845237,0.0001135016],"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":[0.00001252167,0.001492579,0.000006828429,0.00004121789,0.00001879699,0.00008435013,0.0009272074,0.282315,0.1263014,0.02782025,0.0009219503,0.5600579],"study_design_scores_gemma":[0.00006006839,0.0001494119,0.00001138886,0.000009790647,0.000007457821,0.00004544712,0.00008114544,0.8692026,0.1020895,0.0006412087,0.02747679,0.0002252083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001424844,0.00004174528,0.9943479,0.0008488618,0.0006305788,0.0003619101,0.00003475607,0.0004122169,0.001897138],"genre_scores_gemma":[0.9698976,0.000002388274,0.02759818,0.0004956155,0.00009476898,0.0003113588,0.0000390714,0.00002575237,0.001535309],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9684727,"threshold_uncertainty_score":0.8844391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02973550098387782,"score_gpt":0.2484590009846891,"score_spread":0.2187235000008113,"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."}}