{"id":"W3205625221","doi":"10.1109/icra48506.2021.9560882","title":"Evaluating Initialization Methods for Discriminative and Fast-Converging HGMM Point Clouds","year":2021,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Initialization; Discriminative model; Computer science; Cluster analysis; Pattern recognition (psychology); Convergence (economics); Artificial intelligence; Covariance; Gaussian; Algorithm; Mathematics; Statistics","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":[0.004610782,0.001821149,0.0009024931,0.002491752,0.0007521406,0.00153158,0.001704575,0.002248613,0.0009283114],"category_scores_gemma":[0.01945122,0.0008399008,0.001064007,0.002279839,0.001106916,0.001799255,0.001730076,0.001360105,0.0006920677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381497,"about_ca_system_score_gemma":0.002003937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008147504,"about_ca_topic_score_gemma":0.009212699,"domain_scores_codex":[0.9983523,0.0004248768,0.0001586039,0.0003121048,0.0005805313,0.0001715852],"domain_scores_gemma":[0.9947673,0.002318987,0.0005090743,0.0007851628,0.001412562,0.0002069237],"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":[0.0006490917,0.0002019361,0.006273164,0.0004809616,0.0001956247,0.000112157,0.0001922831,0.7649283,0.02163217,0.003764464,0.002444268,0.1991256],"study_design_scores_gemma":[0.00002451319,0.00008630657,0.001290355,0.00003351814,0.00001701227,0.00006330839,0.00005626304,0.981348,0.01555127,0.0009530331,0.0005510801,0.00002528797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1195551,0.0009944002,0.8743971,0.0002167357,0.0001198643,0.000341418,0.0003733623,0.003010335,0.00099179],"genre_scores_gemma":[0.3570399,0.0006470117,0.6391974,0.00009997006,0.00003163466,0.0002843449,0.001671027,0.0005148916,0.0005138515],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008147504,"threshold_uncertainty_score":0.02438444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07228048922598113,"score_gpt":0.4103013314101756,"score_spread":0.3380208421841944,"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."}}