{"id":"W2076965120","doi":"10.1109/3dv.2014.21","title":"Generalized 4-Points Congruent Sets for 3D Registration","year":2014,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RANSAC; Matching (statistics); Base (topology); Point (geometry); Point set registration; Degree (music); Mathematics; Algorithm; Property (philosophy); Computer science; Space (punctuation); Artificial intelligence; Image (mathematics); 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":[],"consensus_categories":[],"category_scores_codex":[0.00009062039,0.00006644618,0.00007580225,0.00002425776,0.00002936159,0.00002831414,0.00003306391,0.00004379003,0.00004546189],"category_scores_gemma":[0.00002776931,0.00006224182,0.00002640287,0.00003387007,0.000006477329,0.00003918624,0.000002402623,0.00002053142,0.00001758175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002228107,"about_ca_system_score_gemma":0.000004417225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000011924,"about_ca_topic_score_gemma":0.00004040405,"domain_scores_codex":[0.9996114,0.000009839401,0.0001316555,0.00008052382,0.00006218621,0.0001043881],"domain_scores_gemma":[0.9997728,0.00002523183,0.0000143878,0.0001104842,0.00004074537,0.00003638745],"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":[0.000009841837,0.00001366156,0.00009011423,0.00006987189,0.00002081505,3.069147e-7,0.00004450312,0.8752555,0.006760845,0.08558499,0.02374098,0.008408536],"study_design_scores_gemma":[0.0003856011,0.00002190219,0.00008040479,0.00000440892,0.000006653923,6.018319e-7,0.000003533288,0.9661492,0.006068726,0.0008429128,0.02634789,0.00008820178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01913122,0.000009662279,0.9720198,0.0001609625,0.0002766402,0.0001599441,0.000002740042,0.0001743582,0.0080647],"genre_scores_gemma":[0.9086673,0.00001248511,0.09005325,0.0002897066,0.0001090898,0.00001908568,0.0001210409,0.00002746226,0.0007005564],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8895361,"threshold_uncertainty_score":0.2538148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0165941211398988,"score_gpt":0.2366617464986449,"score_spread":0.2200676253587461,"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."}}