{"id":"W2272175853","doi":"10.1002/rob.21616","title":"Three‐dimensional Scan Registration using Curvelet Features in Planetary Environments","year":2015,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Neptec Design Group (Canada); University of Waterloo","funders":"","keywords":"Curvelet; Feature (linguistics); Pattern recognition (psychology); Metric (unit); Histogram; Transformation (genetics); Feature extraction; Image registration; Matching (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":[0.0007334631,0.0006516535,0.0008281537,0.002798524,0.0004241483,0.001095803,0.001123787,0.000884528,0.001027545],"category_scores_gemma":[0.002378579,0.0004194725,0.0006472341,0.003372666,0.0006429964,0.001560413,0.001463699,0.000984158,0.001352898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004426698,"about_ca_system_score_gemma":0.000557147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002869219,"about_ca_topic_score_gemma":0.002494448,"domain_scores_codex":[0.9990392,0.0001478332,0.00003950581,0.0002534118,0.000424838,0.00009521013],"domain_scores_gemma":[0.9989628,0.0002417228,0.0001689081,0.0003098849,0.0002594502,0.00005726436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003243113,0.0002655116,0.003846318,0.0000903604,0.00007504877,0.0003785963,0.0003001899,0.1758455,0.04271513,0.005908707,0.004490951,0.7657593],"study_design_scores_gemma":[0.00001753364,0.00008207281,0.00247701,0.00001008998,0.00001185666,0.0002259875,0.00009835775,0.9709095,0.01733428,0.005170926,0.003634546,0.0000277993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09306122,0.0002469998,0.9019716,0.0001470399,0.00005276523,0.00006888167,0.0002264954,0.002593232,0.001631909],"genre_scores_gemma":[0.5747761,0.0004668448,0.4196357,0.00009043245,0.00007985759,0.0001036868,0.001996838,0.0003918333,0.002458836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002869219,"threshold_uncertainty_score":0.005705118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02666331061201527,"score_gpt":0.2306653545073566,"score_spread":0.2040020438953414,"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."}}