{"id":"W2142243548","doi":"10.48550/arxiv.1204.2847","title":"Segmentation Similarity and Agreement","year":2012,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Segmentation; Similarity (geometry); Metric (unit); Computer science; Scale-space segmentation; Artificial intelligence; Edit distance; Pattern recognition (psychology); Image segmentation; Agreement; Segmentation-based object categorization; 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":[0.02922136,0.001408866,0.001939,0.01039024,0.001817236,0.005890527,0.002930358,0.003021255,0.004936952],"category_scores_gemma":[0.1477778,0.000831846,0.001844083,0.006962569,0.004229046,0.009738747,0.006161086,0.002208356,0.002821451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002002117,"about_ca_system_score_gemma":0.001539587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001900997,"about_ca_topic_score_gemma":0.002485276,"domain_scores_codex":[0.9339591,0.02172718,0.007696694,0.01291866,0.02191864,0.001779717],"domain_scores_gemma":[0.8541687,0.07668695,0.01268672,0.01784084,0.03643902,0.002177732],"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":[0.002973271,0.0003293656,0.1006572,0.002780818,0.001829766,0.000732849,0.00995884,0.05514819,0.06930561,0.06519295,0.01871827,0.6723728],"study_design_scores_gemma":[0.0002207766,0.001783251,0.1313404,0.0007319716,0.001136776,0.003607615,0.006312966,0.4430799,0.1187699,0.2323204,0.05974159,0.0009544789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1009424,0.001873707,0.8708186,0.000405769,0.0004259943,0.00052395,0.001300638,0.00202291,0.02168619],"genre_scores_gemma":[0.7063667,0.000506933,0.2835647,0.0002786656,0.0002291589,0.0006684719,0.002850544,0.001403872,0.004130984],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02922136,"threshold_uncertainty_score":0.1545392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05867959867732957,"score_gpt":0.2023831825991733,"score_spread":0.1437035839218437,"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."}}