{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004963452,0.0006280465,0.001798026,0.0002231923,0.00004856114,0.00007227291,0.0002985341,0.0004582307,0.00009929496],"category_scores_gemma":[0.0003084195,0.0006096534,0.0005220149,0.0006688494,0.0000419549,0.0001399654,0.00002496694,0.0003573082,0.0002353607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002622871,"about_ca_system_score_gemma":0.0001833708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001239699,"about_ca_topic_score_gemma":0.00007564835,"domain_scores_codex":[0.9965275,0.0002333596,0.001800731,0.0006075578,0.0005155917,0.0003152411],"domain_scores_gemma":[0.9974284,0.0001793382,0.0007176634,0.001276426,0.0002254259,0.0001727663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000244226,0.0000914758,0.000002852925,0.4422701,0.0004876925,0.00005191818,0.0003135317,0.05321396,0.00003339932,0.002763932,0.1323264,0.3684203],"study_design_scores_gemma":[0.0001447754,0.00008802988,0.00000229173,0.09632702,0.0007485593,0.00001911094,0.00002343965,0.005794087,0.00001695633,0.00006676155,0.8961266,0.0006423854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001610247,0.98744,0.006050524,0.0001795907,0.000655416,0.001986504,0.0003206978,0.0002269317,0.003124246],"genre_scores_gemma":[0.00006037475,0.9935657,0.001516573,0.0001675041,0.0003461974,0.00005562957,0.00356881,0.000135536,0.0005836533],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7638002,"threshold_uncertainty_score":0.9996355,"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."}}