{"id":"W2170299882","doi":"10.1109/34.993557","title":"Geometric probing of dense range data","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Tree traversal; Computer science; Template; Artificial intelligence; Voxel; Binary tree; Interval tree; Tree (set theory); Pattern recognition (psychology); Template matching; Pixel; Intersection (aeronautics); Computer vision; Tree structure; Mathematics; Algorithm; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001126561,0.0001340666,0.0002429883,0.0006815868,0.00005702876,0.00002804875,0.0001766659,0.0000482484,0.0003783743],"category_scores_gemma":[0.000004398961,0.0001243365,0.00009232549,0.00131681,0.00003008769,0.00009444325,0.000001975725,0.000130226,0.00001609771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001534001,"about_ca_system_score_gemma":0.000001654968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002824908,"about_ca_topic_score_gemma":0.0004086695,"domain_scores_codex":[0.9991412,0.00002374355,0.0003174604,0.0002257964,0.0001578237,0.0001339955],"domain_scores_gemma":[0.9993502,0.00007012898,0.00004169163,0.0004389441,0.00003797847,0.00006103424],"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":[0.000001936286,0.00005540154,0.0005220318,0.00003747318,0.0002753125,0.000002436563,0.00008457497,0.6767141,0.0002018065,0.000001523354,0.00001453459,0.3220888],"study_design_scores_gemma":[0.00005829645,0.00002976715,0.0002617119,0.00001887366,0.0004510813,0.000002691019,0.00001871118,0.9662737,0.03271846,0.000005364814,0.00003179552,0.0001295622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01167106,0.0005389736,0.9873828,0.00003051545,0.00008704879,0.00007442696,0.00009061892,0.00005279576,0.00007178972],"genre_scores_gemma":[0.9975179,0.001975071,0.0003677001,0.00003473586,0.00001074637,0.000003416855,0.000015068,0.00001600099,0.00005938073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9870151,"threshold_uncertainty_score":0.5070295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042507823116855,"score_gpt":0.2480962713742439,"score_spread":0.2076711931430754,"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."}}