{"id":"W2792671280","doi":"10.1155/2019/7293193","title":"Image Evolution Using 2D Power Spectra","year":2019,"lang":"en","type":"article","venue":"Complexity","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Heuristics; Genetic programming; Metric (unit); Pattern recognition (psychology); Image (mathematics); Perception; Field (mathematics); Machine learning; Computer vision; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000117192,0.00008824806,0.0000982101,0.00004859292,0.000165573,0.00006742729,0.0005000259,0.00003074123,0.0003035917],"category_scores_gemma":[0.000005981691,0.00008961748,0.00005670743,0.0003142903,0.00007105937,0.0004547483,0.0001991045,0.00009979466,0.001033127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211646,"about_ca_system_score_gemma":0.00006096548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006294474,"about_ca_topic_score_gemma":0.000002373987,"domain_scores_codex":[0.9991622,0.00002805344,0.0001327888,0.0003015052,0.0001673051,0.0002081594],"domain_scores_gemma":[0.9992036,0.00002225913,0.0000544774,0.0005846851,0.00007239779,0.00006259878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000150596,0.00009849355,0.001490339,0.000005973228,0.000006438351,0.000001688895,0.000104733,0.00005205875,0.01530837,0.9814394,0.001196189,0.0002948542],"study_design_scores_gemma":[0.0002504098,0.00004178918,0.1405634,0.000009996872,0.00000258508,0.00003846217,0.00002509293,0.707038,0.0002996242,0.1465798,0.004914309,0.0002364831],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1278221,0.00005812625,0.8570519,0.0005454678,0.0002495903,0.0001702921,0.000006091954,0.0001601522,0.01393622],"genre_scores_gemma":[0.6461548,7.819551e-7,0.3534934,0.00007256148,0.00005164283,0.000003470991,0.000003418557,0.00000462807,0.0002153539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8348596,"threshold_uncertainty_score":0.9997447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0378402936208699,"score_gpt":0.2797179422517128,"score_spread":0.2418776486308429,"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."}}