{"id":"W2073077044","doi":"10.1109/tim.2003.817910","title":"Registration of range measurements with compact surface representation","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Representation (politics); Computation; Range (aeronautics); Feature extraction; Translation (biology); Rotation (mathematics); Algorithm; Engineering","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":[0.0006768645,0.001081053,0.001374619,0.002063019,0.0002344479,0.001451578,0.001104407,0.0009140382,0.001544032],"category_scores_gemma":[0.004926654,0.0007124043,0.0008231935,0.002042247,0.0006770691,0.002262665,0.002143849,0.001009897,0.001301932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003141791,"about_ca_system_score_gemma":0.0004558136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006334034,"about_ca_topic_score_gemma":0.0005630578,"domain_scores_codex":[0.9980226,0.0003806807,0.0001017823,0.0003601266,0.001047963,0.00008686545],"domain_scores_gemma":[0.9981382,0.0004727258,0.0002431519,0.0007596653,0.0003505811,0.00003568092],"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":[0.0003774724,0.00009572082,0.001251517,0.0002532918,0.00009124306,0.0002069856,0.0004406604,0.1011587,0.1466827,0.01620164,0.002030136,0.7312099],"study_design_scores_gemma":[0.00003521376,0.000231709,0.00177429,0.00002400392,0.00002967409,0.0006390899,0.0001546787,0.9090628,0.07042022,0.01061235,0.006941537,0.0000744052],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008428392,0.00006500989,0.9899544,0.00001990224,0.00001740275,0.00002187725,0.00002869978,0.001044275,0.0004200229],"genre_scores_gemma":[0.2859023,0.0002442614,0.7115462,0.0000500619,0.00006309758,0.0001717301,0.0006264739,0.0004059031,0.0009899266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002063019,"threshold_uncertainty_score":0.005165279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06176394765843232,"score_gpt":0.2485804124393141,"score_spread":0.1868164647808817,"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."}}