{"id":"W2347679396","doi":"","title":"Double Threshold Image Segmentation Based on Two-layer Genetic Algorithm","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Image segmentation; Genetic algorithm; Emulation; Artificial intelligence; Segmentation; Scale-space segmentation; Image (mathematics); Image processing; Segmentation-based object categorization; Algorithm; Computer vision; Tracing; Population; Minimum spanning tree-based segmentation; Pattern recognition (psychology); Machine learning","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":[0.0000574721,0.0001475957,0.0001045165,0.0001123982,0.0001678981,0.00002402052,0.0001164768,0.00003946484,0.00004197796],"category_scores_gemma":[9.71109e-8,0.0001594054,0.00005571472,0.0002428481,0.00002739413,0.00008047378,0.00001237855,0.0001186175,0.0001953876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007517898,"about_ca_system_score_gemma":0.00001195485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002262408,"about_ca_topic_score_gemma":6.893065e-7,"domain_scores_codex":[0.99927,0.00001082222,0.0001852622,0.0002201676,0.0001361694,0.000177612],"domain_scores_gemma":[0.9995902,0.00002155371,0.00002660468,0.0002437577,0.00005259555,0.0000652923],"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":[0.0000111251,0.0001084356,0.0001412748,0.00002679596,0.00002431334,0.0000036708,0.0001321242,0.3001232,0.400782,0.00004372905,0.002682379,0.2959209],"study_design_scores_gemma":[0.001999972,0.00003695691,0.001132313,0.00001012989,0.00001551314,0.00002226702,0.000009580474,0.3959423,0.5091697,0.0003122105,0.09097139,0.0003776636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003696094,0.00007244974,0.9927381,0.00002499998,0.00004977419,0.0005702876,0.000006476934,0.0004458972,0.002395918],"genre_scores_gemma":[0.02007808,0.00001734352,0.9787109,0.0001986925,0.0002447505,0.0005734777,0.00002736111,0.00003699607,0.0001123624],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2955433,"threshold_uncertainty_score":0.6500363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02777272925184638,"score_gpt":0.2796983582117079,"score_spread":0.2519256289598615,"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."}}