{"id":"W1998076850","doi":"10.5244/c.22.16","title":"Parameter Selection for Graph Cut Based Image Segmentation","year":2008,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Cut; Segmentation-based object categorization; Segmentation; Image segmentation; Scale-space segmentation; Artificial intelligence; Computer science; Pattern recognition (psychology); AdaBoost; Graph; Minimum spanning tree-based segmentation; Feature selection; Classifier (UML); Computer vision; Theoretical computer science","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":[0.003231621,0.002120832,0.001692579,0.004177373,0.0009247432,0.002560032,0.002078944,0.00307618,0.002906822],"category_scores_gemma":[0.01184303,0.0010436,0.001697829,0.002303476,0.001307995,0.002165281,0.001228524,0.002225108,0.001782869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290849,"about_ca_system_score_gemma":0.0009930275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002853454,"about_ca_topic_score_gemma":0.003098599,"domain_scores_codex":[0.9980666,0.000585441,0.0001465251,0.0004862469,0.0005677721,0.0001473893],"domain_scores_gemma":[0.9963193,0.002119436,0.0003346912,0.0002883662,0.0008407898,0.00009744402],"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":[0.0003687912,0.0002342939,0.002661219,0.0005509898,0.0002200849,0.0002985579,0.0003753394,0.3781099,0.03998972,0.008304164,0.007671597,0.5612153],"study_design_scores_gemma":[0.00003550745,0.0001109961,0.0007494541,0.00007462129,0.00006544436,0.0002105625,0.0001112424,0.9665883,0.0166467,0.01119182,0.004167636,0.00004777025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01315261,0.0007611946,0.9815563,0.0001940137,0.0000516364,0.0002011523,0.0001036421,0.002756035,0.001223354],"genre_scores_gemma":[0.205496,0.0006391522,0.7894108,0.0002745852,0.00006096917,0.0005647087,0.0008717209,0.001370563,0.001311451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004177373,"threshold_uncertainty_score":0.01709062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02694813217863968,"score_gpt":0.2984128017541642,"score_spread":0.2714646695755245,"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."}}