{"id":"W2023528786","doi":"10.1142/s0219467804001415","title":"AUTOMATIC IMAGE REGISTRATION USING VIRTUAL CIRCLES","year":2004,"lang":"en","type":"article","venue":"International Journal of Image and Graphics","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Universidade do Porto; University of Toronto; Purdue University; National Aeronautics and Space Administration","keywords":"Computer vision; Computer science; Artificial intelligence; Similarity (geometry); Enhanced Data Rates for GSM Evolution; Set (abstract data type); Pixel; Image registration; RADIUS; Image (mathematics); Virtual image; Computer graphics (images)","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":[],"consensus_categories":[],"category_scores_codex":[0.0004501832,0.00008569511,0.0001176607,0.0003074582,0.00005319683,0.0003387691,0.0005517307,0.0000404062,0.00001461863],"category_scores_gemma":[0.000229714,0.0000774155,0.00007414946,0.0001564112,0.0001441058,0.001760689,0.0000807863,0.0001744361,0.000002193933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000540414,"about_ca_system_score_gemma":0.0001300384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002268458,"about_ca_topic_score_gemma":0.000002517326,"domain_scores_codex":[0.9986643,0.00003978744,0.0004430962,0.0001166753,0.0006400473,0.00009606688],"domain_scores_gemma":[0.9987516,0.0000594084,0.0004038207,0.0001144744,0.0005777547,0.00009289582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004042648,0.0005100655,0.0005539393,0.00005046416,0.0003545923,0.001873472,0.00278496,0.00006172323,0.5087922,0.1017322,0.001963373,0.3812826],"study_design_scores_gemma":[0.007210082,0.001448308,0.01645244,0.001407283,0.0001339547,0.009870935,0.00083191,0.06300421,0.5559537,0.3420559,0.0005492445,0.00108209],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.105076,0.00006854314,0.892531,0.001854326,0.0003094179,0.00004133525,0.000001855687,0.00003645739,0.00008108765],"genre_scores_gemma":[0.4714468,0.0001875862,0.5273716,0.0008306918,0.0001478439,8.084215e-7,0.000001603542,0.000006063103,0.000006954045],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3802005,"threshold_uncertainty_score":0.3266758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693232691643445,"score_gpt":0.3130827615800261,"score_spread":0.2961504346635916,"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."}}