{"id":"W2185581835","doi":"","title":"Active 3D sensing","year":2000,"lang":"en","type":"article","venue":"","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Triangulation; Artificial intelligence; Active vision; Computer vision; Computer graphics; Cover (algebra); Graphics; Computer graphics (images); Engineering; Geography","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000051759,0.00004242334,0.00004420613,0.00000618803,0.00008539676,0.00002312296,0.00003493289,0.00001960244,0.06100686],"category_scores_gemma":[0.000003416186,0.00002794241,0.00001673174,0.00006207709,0.00001665821,0.00009674352,6.253254e-7,0.00004256358,0.003204842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":6.622614e-7,"about_ca_system_score_gemma":0.000004687732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750836,"about_ca_topic_score_gemma":0.002196399,"domain_scores_codex":[0.9996584,0.00002788808,0.00004392245,0.00008510386,0.00006626712,0.0001184058],"domain_scores_gemma":[0.9998656,0.00002694088,0.000005299422,0.00005093114,0.000006741751,0.00004447446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000009621191,0.000001108744,0.01215645,5.855371e-7,0.000002378697,0.000005686223,0.0001109,0.0001424891,0.000009788653,0.000001749296,0.0004677749,0.9870915],"study_design_scores_gemma":[0.0001372152,0.00005187599,0.9204023,0.000006861798,0.000003848516,0.00003168676,0.0003359191,0.01084517,0.0002878789,0.0001890886,0.06751496,0.0001931353],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5896094,0.00002657613,0.000007329543,0.00004761091,0.00003697977,0.00001508164,0.000005054976,0.00004108481,0.4102109],"genre_scores_gemma":[0.979538,0.00001210657,0.001112216,0.0002762436,0.0000425925,1.355917e-8,0.00002183732,6.678824e-7,0.01899637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9868983,"threshold_uncertainty_score":0.9975713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01534106032077015,"score_gpt":0.1973679980769817,"score_spread":0.1820269377562116,"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."}}