{"id":"W2921073965","doi":"10.3390/s19051191","title":"A Review of Point Set Registration: From Pairwise Registration to Groupwise Registration","year":2019,"lang":"en","type":"review","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pairwise comparison; Image registration; Computer science; Point (geometry); Set (abstract data type); Point set registration; Artificial intelligence; Data set; Data mining; Computer vision; Mathematics; Image (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":[0.001872185,0.001479126,0.002114302,0.006190622,0.0004900084,0.001805005,0.002014637,0.001846967,0.005809862],"category_scores_gemma":[0.005476349,0.0009523247,0.00135188,0.008495434,0.001140293,0.003091966,0.00134462,0.001406705,0.004722258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007636779,"about_ca_system_score_gemma":0.001893511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002091638,"about_ca_topic_score_gemma":0.001761856,"domain_scores_codex":[0.9989237,0.0002030095,0.0001878586,0.0002668932,0.0003729305,0.00004551854],"domain_scores_gemma":[0.9973738,0.001639399,0.0001955269,0.000149106,0.0005847396,0.00005731926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004169865,0.00003188268,0.0002632989,0.01716341,0.0001065459,0.0001167914,0.00009458037,0.001612509,0.001442293,0.006975673,0.02063333,0.9515181],"study_design_scores_gemma":[0.00001614315,0.0001747162,0.001474314,0.007549178,0.0003249433,0.00239782,0.0001820015,0.002835175,0.003156983,0.01317369,0.9685742,0.0001408122],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003330625,0.974861,0.02027811,0.0004796164,0.0005418247,0.00003013407,0.0001488199,0.0001367848,0.003190669],"genre_scores_gemma":[0.003425111,0.9757285,0.01784434,0.0004069693,0.0006905366,0.00006273863,0.0003509273,0.00006285636,0.001428081],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006190622,"threshold_uncertainty_score":0.01943594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05631782226594738,"score_gpt":0.2976563125164667,"score_spread":0.2413384902505193,"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."}}