{"id":"W2365338663","doi":"","title":"An Improved GVF Snake Based on Multi-scale Image Analysis","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vector flow; Computer science; Artificial intelligence; Active contour model; Computer vision; Noise (video); Image (mathematics); Image segmentation; Scale (ratio); Segmentation; Enhanced Data Rates for GSM Evolution; Pattern recognition (psychology); Edge detection; Image gradient; Image processing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007010554,0.0006552606,0.001299788,0.001246328,0.0003097816,0.0006340484,0.001480411,0.001565273,0.001771104],"category_scores_gemma":[0.0009408018,0.0005283306,0.001244062,0.001335562,0.0004860466,0.001453258,0.0007724359,0.0007981627,0.0007651085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003988644,"about_ca_system_score_gemma":0.0005764834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002290134,"about_ca_topic_score_gemma":0.001532616,"domain_scores_codex":[0.9995298,0.00006765374,0.00002364136,0.0001098034,0.0002311496,0.00003793714],"domain_scores_gemma":[0.9997378,0.00005568168,0.00002664931,0.00005428418,0.0001033621,0.00002219294],"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":[0.0001862202,0.0001068749,0.000811492,0.0002649867,0.0001233129,0.000340841,0.0001929155,0.2271789,0.1339,0.02254454,0.007189291,0.6071606],"study_design_scores_gemma":[0.00002831917,0.00008314797,0.0004853923,0.00001332498,0.00002987817,0.0003819998,0.000008252509,0.9778325,0.009689283,0.003741491,0.007661901,0.00004450976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003535111,0.0002699011,0.9946908,0.00008151462,0.00006461376,0.0000297782,0.0000241839,0.0007139623,0.0005900611],"genre_scores_gemma":[0.1435835,0.0007048874,0.850545,0.0001662894,0.0001033564,0.0001343315,0.0002786545,0.0002629023,0.0042211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002290134,"threshold_uncertainty_score":0.005924881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006544898076226144,"score_gpt":0.2625357948179153,"score_spread":0.2559908967416892,"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."}}