{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002600928,0.0001413592,0.0001400659,0.00008895368,0.00009030486,0.00002913488,0.00002887024,0.00004439989,0.00005890458],"category_scores_gemma":[0.000003497366,0.0001352886,0.00003288955,0.0001812962,0.00003487143,0.0001601994,9.009462e-8,0.00007993368,0.000002883684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002151509,"about_ca_system_score_gemma":0.00004637734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002434769,"about_ca_topic_score_gemma":0.001172198,"domain_scores_codex":[0.9987678,0.00006581927,0.0002964257,0.0001565125,0.0005917811,0.0001216575],"domain_scores_gemma":[0.9995413,0.00001226855,0.00007282685,0.0001407252,0.0001654765,0.00006737716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009347384,0.0001336667,0.002562239,0.00007476904,0.0001237981,5.32536e-7,0.0006248667,0.9496234,0.04351195,0.0001607145,0.00009354618,0.002997016],"study_design_scores_gemma":[0.003601055,0.0003959134,0.005393083,0.0001650151,0.0001504096,0.00001072127,0.0006513257,0.01724927,0.9716681,0.00006490755,0.0002993918,0.0003507741],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.407406,0.00002810803,0.5884182,0.00003534663,0.0002641649,0.0003752852,0.000005242373,0.00006654002,0.003401159],"genre_scores_gemma":[0.9984682,0.00004551219,0.001357536,0.0000226067,0.000004180593,0.000009182347,0.000005337678,0.0000184957,0.00006896773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9323742,"threshold_uncertainty_score":0.5516908,"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."}}