{"id":"W2092705708","doi":"10.1145/641865.641868","title":"View planning for automated three-dimensional object reconstruction and inspection","year":2003,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":449,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; National Research Council Canada","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Triangulation; Process (computing); Object (grammar); Frame (networking); 3D reconstruction; Set (abstract data type); Range (aeronautics); Reference frame; Task (project management)","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":[0.0007945242,0.0003771624,0.001011111,0.0001264805,0.0003419499,0.00006714125,0.0001814741,0.0002024547,0.000004683104],"category_scores_gemma":[0.0002468509,0.000336595,0.0001879186,0.0002971106,0.0001171366,0.00006956716,0.0001993172,0.0003949067,0.000008078622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006986313,"about_ca_system_score_gemma":0.00007427343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003435509,"about_ca_topic_score_gemma":0.000002481373,"domain_scores_codex":[0.998264,0.0002780827,0.0004957038,0.000530158,0.00009926394,0.0003327999],"domain_scores_gemma":[0.9977893,0.001272536,0.0004120223,0.0003907228,0.00009087304,0.0000444942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[7.667081e-7,0.00001218903,0.0003230587,0.0005170866,0.0001026685,7.496038e-7,0.000003284836,0.0001736512,3.156908e-7,0.0005972102,0.0001072684,0.9981617],"study_design_scores_gemma":[0.0025692,0.0006195246,0.002417098,0.07213357,0.002245933,0.0005941048,0.00009407142,0.1366682,0.00003774354,0.08123963,0.6954636,0.005917293],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.0008511886,0.9114317,0.08373158,0.00001180312,0.0009750658,0.0009292598,0.00004315678,0.001836734,0.0001894786],"genre_scores_gemma":[0.007745317,0.30333,0.6857848,0.00003617763,0.001321038,0.000112414,0.001139508,0.0004420951,0.00008863468],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9922445,"threshold_uncertainty_score":0.9999086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06202612982393969,"score_gpt":0.3522336579984698,"score_spread":0.2902075281745302,"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."}}