{"id":"W2912696013","doi":"10.1016/j.media.2005.09.002","title":"United Snakes","year":2005,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":122,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Turun Yliopisto","keywords":"Computer science; Artificial intelligence; Robustness (evolution); Segmentation; Computer vision; Image segmentation; Pattern recognition (psychology); Biology","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":[0.0007584036,0.0009553255,0.000881983,0.002825575,0.001346737,0.002617329,0.001309568,0.00240151,0.06153904],"category_scores_gemma":[0.002061022,0.0008893713,0.001191834,0.001467661,0.0008570395,0.002823024,0.003161039,0.001704306,0.02473514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005134162,"about_ca_system_score_gemma":0.0006211483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009603176,"about_ca_topic_score_gemma":0.001485366,"domain_scores_codex":[0.9993836,0.0001026371,0.0000308885,0.000223204,0.0001887653,0.00007100814],"domain_scores_gemma":[0.9993227,0.00009968286,0.00003360745,0.0002790904,0.0001821413,0.00008282573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003000668,0.000107398,0.0005317617,0.0001901188,0.00009374459,0.0002464447,0.0001637421,0.01452877,0.01275036,0.1686989,0.06901668,0.733372],"study_design_scores_gemma":[0.0001069921,0.0001691797,0.001232209,0.0002638731,0.0001308412,0.001867193,0.0001606697,0.2781371,0.03734424,0.1524811,0.5280066,0.0001000121],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01360099,0.002764599,0.7749289,0.001428425,0.001058928,0.000189583,0.0009566013,0.01060884,0.1944631],"genre_scores_gemma":[0.2077677,0.002577074,0.5133508,0.001315134,0.0004244625,0.0003406943,0.004313749,0.003757576,0.266153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06153904,"threshold_uncertainty_score":0.2058686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048284823935208,"score_gpt":0.3051294323258833,"score_spread":0.2946465840865312,"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."}}