{"id":"W2338718259","doi":"","title":"Tissue Segmentation in Medical Images Based on Image Processing Chain Optimization","year":2010,"lang":"en","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Artificial intelligence; Image processing; Computer vision; Segmentation; Image segmentation; Feature (linguistics); Sample (material); Pattern recognition (psychology); Feature extraction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001066453,0.0006885644,0.0008969008,0.0008945471,0.0003441003,0.0007371777,0.000647797,0.0009747517,0.001165084],"category_scores_gemma":[0.001570092,0.0004821985,0.0006262246,0.0008965656,0.0006878148,0.0007745536,0.0007112965,0.0005767013,0.000394958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008105093,"about_ca_system_score_gemma":0.0006859276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002167342,"about_ca_topic_score_gemma":0.001993044,"domain_scores_codex":[0.9996313,0.00009304017,0.00002734622,0.00009809099,0.0001195775,0.00003081373],"domain_scores_gemma":[0.9995605,0.0002276068,0.00006150272,0.00004287436,0.0000917759,0.00001571176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001163258,0.00004340689,0.00098015,0.0001240386,0.00005516203,0.00006470711,0.0001077132,0.8014219,0.02791286,0.003910803,0.0004637598,0.1647991],"study_design_scores_gemma":[0.000003243778,0.00002200415,0.0002109648,0.000004090771,0.000006019205,0.00002263463,0.000004893397,0.9939826,0.004327163,0.001101722,0.000311619,0.000003074746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0173485,0.0001265602,0.9813106,0.00006685813,0.000007438874,0.00004643351,0.0000143969,0.0003734271,0.0007057058],"genre_scores_gemma":[0.2550652,0.0002754126,0.7418969,0.00007562919,0.0000210559,0.0001840871,0.0001458602,0.0001580054,0.002177923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002167342,"threshold_uncertainty_score":0.005880654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00658104212227689,"score_gpt":0.2803728311839042,"score_spread":0.2737917890616273,"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."}}