{"id":"W2124498492","doi":"10.1109/icsmc.2007.4414078","title":"Invariant feature set in convex hull for fast image registration","year":2007,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Windsor","funders":"","keywords":"Convex hull; Mathematics; Artificial intelligence; Computer vision; Convex set; Quadrilateral; Diagonal; Regular polygon; Computer science; Geometry; Convex optimization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008770937,0.00007488044,0.00009098327,0.00009734366,0.00003152893,0.0001036935,0.0003439575,0.00006999406,0.00004406387],"category_scores_gemma":[0.0001337711,0.00006516367,0.00002580567,0.0002305558,0.00003833033,0.0005100001,0.00005275157,0.0001022231,0.00001359488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000432119,"about_ca_system_score_gemma":0.00004399711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004502681,"about_ca_topic_score_gemma":0.0001323595,"domain_scores_codex":[0.9991496,0.00002397026,0.0002057177,0.0002345983,0.0001940824,0.0001920173],"domain_scores_gemma":[0.9994134,0.0001148698,0.00006697261,0.0002559761,0.0000736155,0.00007520176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000494745,0.0001977494,0.0003613942,0.0001087626,0.0000134707,0.0001500158,0.002719025,0.000001279839,0.2134263,0.176259,0.3694021,0.2373113],"study_design_scores_gemma":[0.001371503,0.0002449825,0.00349791,0.00004941778,0.000004044317,0.00003383943,0.000401888,0.018379,0.9572068,0.0114758,0.006966503,0.0003682782],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003517961,0.000007351342,0.9895348,0.00272262,0.00008560477,0.0003659909,0.000002258471,0.0001946852,0.006734884],"genre_scores_gemma":[0.03652872,0.0000037586,0.9587096,0.002447683,0.00004737016,0.00002677774,0.00002157879,0.000005445529,0.002209089],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7437805,"threshold_uncertainty_score":0.2657298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161485351463198,"score_gpt":0.3186812333584569,"score_spread":0.2970663798438249,"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."}}