{"id":"W2139744456","doi":"10.1109/icsmc.1995.538258","title":"An introduction to panospheric imaging","year":2002,"lang":"en","type":"article","venue":"","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Computer vision; Computer graphics (images); Virtual reality; Artificial intelligence; Observer (physics); Process (computing); Perspective (graphical); Orientation (vector space); Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005850861,0.001053766,0.0006067531,0.002131805,0.0008788355,0.002477786,0.001127495,0.002237585,0.02609134],"category_scores_gemma":[0.001354343,0.0005750259,0.0006278151,0.002870905,0.001597087,0.003462038,0.001590613,0.003561094,0.01376199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000655942,"about_ca_system_score_gemma":0.0005939456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056089,"about_ca_topic_score_gemma":0.001390158,"domain_scores_codex":[0.9994975,0.00009537269,0.00003875703,0.0001260276,0.0001932734,0.00004902339],"domain_scores_gemma":[0.9994037,0.0002292832,0.00002970305,0.00006288905,0.0002208602,0.00005354541],"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":[0.00007888629,0.00009258582,0.0008294019,0.001698128,0.00004562837,0.0007907803,0.0005060796,0.00319033,0.005695209,0.2429028,0.2016382,0.542532],"study_design_scores_gemma":[0.000002781167,0.00003400521,0.000389602,0.0002245318,0.000005895653,0.001071244,0.00007073938,0.00108106,0.0004166487,0.04412172,0.9525582,0.00002352742],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002518218,0.32311,0.3518427,0.007512348,0.02337248,0.0002264762,0.0009450734,0.00156591,0.2889069],"genre_scores_gemma":[0.04406979,0.3995929,0.2570827,0.01041043,0.03153257,0.000445539,0.002055806,0.001061949,0.2537484],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02609134,"threshold_uncertainty_score":0.08728421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007134419955733422,"score_gpt":0.2072930825253328,"score_spread":0.2001586625695994,"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."}}