{"id":"W4390720453","doi":"10.1017/9781009299909.011","title":"Pose-and-Point Estimation Problems","year":2024,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Bundle adjustment; Artificial intelligence; Computer vision; Simultaneous localization and mapping; Point (geometry); Computer science; Trajectory; Pose; Motion (physics); State (computer science); Robot; Mathematics; Algorithm; Mobile robot; Image (mathematics); Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004005999,0.0002588667,0.0002174585,0.0001661328,0.00006111955,0.00006502706,0.0001075426,0.0002591313,0.0000028718],"category_scores_gemma":[0.000002218438,0.0003092687,0.00008024004,0.000007085956,0.00006347409,0.00005901511,0.00007567897,0.00028549,0.00003323279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001412007,"about_ca_system_score_gemma":0.00001671682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002003811,"about_ca_topic_score_gemma":0.00000128996,"domain_scores_codex":[0.999311,0.000005623113,0.0001428283,0.0002561191,0.00013419,0.0001501852],"domain_scores_gemma":[0.9995762,0.00002033463,0.00003894081,0.000218925,0.00005175537,0.00009386385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005433805,0.00000168217,1.557626e-7,0.0005263901,0.0001026791,0.00008194925,0.00004851112,0.04347822,0.00006513338,0.9414199,0.01280455,0.00146538],"study_design_scores_gemma":[0.0001880638,0.00002618922,0.000001605006,0.0003894195,0.0002187379,0.00001499558,0.000006834284,0.3655553,0.0001864706,0.0001620016,0.6328541,0.0003963213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00004462374,0.0003657671,0.02164351,0.00001177409,0.0003491478,0.0002878769,0.00009982658,0.0004583977,0.976739],"genre_scores_gemma":[0.003097229,0.0002314411,0.0003601323,0.00001305508,0.00007866071,5.096934e-7,0.0001100799,0.00008237272,0.9960265],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9412579,"threshold_uncertainty_score":0.9999359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282849325827282,"score_gpt":0.1693421857429941,"score_spread":0.1565136924847212,"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."}}