{"id":"W2116060502","doi":"10.1109/icip.2004.1418814","title":"Joint dense 3D interpretation and multiple motion segmentation of temporal image sequences: a variational framework with active curve evolution and level sets","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Joint (building); Segmentation; Interpretation (philosophy); Image segmentation; Artificial intelligence; Motion (physics); Computer vision; Computer science; 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":[0.0008299806,0.0006520766,0.0007684643,0.0008598919,0.0003059253,0.00108369,0.001261365,0.001173519,0.0009264488],"category_scores_gemma":[0.002111951,0.0007772023,0.001009306,0.000722373,0.001326515,0.001644396,0.001453186,0.001152612,0.0002168945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007694414,"about_ca_system_score_gemma":0.001066286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002564293,"about_ca_topic_score_gemma":0.002904914,"domain_scores_codex":[0.9997001,0.00007796243,0.00001661402,0.00006890003,0.0001123505,0.0000241768],"domain_scores_gemma":[0.9994864,0.0002749013,0.00007637055,0.00006595002,0.00006121284,0.00003506296],"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":[0.00007692254,0.00004233636,0.0005666466,0.0002304091,0.00008113893,0.0001893328,0.0003593512,0.6849272,0.02939909,0.1442301,0.0007870861,0.1391103],"study_design_scores_gemma":[0.000004264488,0.0000135451,0.00008793054,0.000008731839,0.000005384159,0.00004785157,0.00001215489,0.9795425,0.001685427,0.01754904,0.001034687,0.000008495907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001770873,0.00005780601,0.9978874,0.00003930293,0.000005512925,0.000007800993,0.000007805971,0.00003419586,0.0001892901],"genre_scores_gemma":[0.1212557,0.0003151391,0.8765338,0.00005024617,0.00004928861,0.00008788673,0.00008306613,0.0001260035,0.00149882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002564293,"threshold_uncertainty_score":0.00558269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02314310383907094,"score_gpt":0.2845443865560426,"score_spread":0.2614012827169717,"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."}}