{"id":"W2164213525","doi":"10.1109/iccv.1995.466850","title":"Topologically adaptable snakes","year":2002,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":337,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Grid; Subdivision; Segmentation; Python (programming language); Merge (version control); Artificial intelligence; Representation (politics); Topology (electrical circuits); Image segmentation; Parametric statistics; Computer vision; Theoretical computer science; Mathematics; Geography; Geometry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009715339,0.00004845586,0.00005815202,0.00003002802,0.00004101595,0.00007139673,0.0004748933,0.00002798149,0.005559643],"category_scores_gemma":[0.00005609126,0.00003500554,0.00002106861,0.0001456645,0.0000370703,0.0003128079,0.0001014365,0.00005205855,0.0004736167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009983876,"about_ca_system_score_gemma":0.000003488741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001064185,"about_ca_topic_score_gemma":0.000001105715,"domain_scores_codex":[0.9993994,0.00002484998,0.0001069244,0.0001599232,0.000172255,0.000136641],"domain_scores_gemma":[0.9995877,0.00004229591,0.00002017973,0.0002484833,0.00002718828,0.00007415653],"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":[3.512424e-7,0.000104889,0.00010875,0.000003329161,0.000004678259,0.00002811248,0.0001952648,0.000001132952,0.004467195,0.1319943,0.2271625,0.6359295],"study_design_scores_gemma":[0.001002345,0.0008323563,0.001685863,0.00002898066,0.000008106945,0.00011178,0.0001563572,0.2292492,0.5769594,0.05490894,0.1340177,0.001038954],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008575465,0.00004954978,0.8637194,0.002141736,0.00005729749,0.00004891229,8.85323e-8,0.0005730627,0.1333242],"genre_scores_gemma":[0.06307022,0.00003868654,0.9144322,0.004707553,0.00002402642,0.00001226914,2.64453e-7,0.00000228632,0.01771253],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6348906,"threshold_uncertainty_score":0.9953494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04028086866436647,"score_gpt":0.242660448145181,"score_spread":0.2023795794808145,"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."}}