{"id":"W2045837255","doi":"10.1109/tgrs.2011.2152849","title":"Geolocation of Argus Flight Data","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Spacecraft Design and Technology","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Aeronautics and Space Institute","keywords":"Argus; Geolocation; Computer science; Remote sensing; Focus (optics); Position (finance); Physics; Geology; Optics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002994287,0.000320521,0.000207828,0.001403153,0.0004958372,0.0005197446,0.0004600438,0.0002858012,0.003268344],"category_scores_gemma":[0.001420928,0.0001354231,0.000154974,0.001342417,0.0002706765,0.00049166,0.0006666505,0.0003785571,0.001639046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006814782,"about_ca_system_score_gemma":0.0007254633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051002,"about_ca_topic_score_gemma":0.01471691,"domain_scores_codex":[0.9996691,0.00005380973,0.00001768037,0.00006702454,0.0001532386,0.00003921867],"domain_scores_gemma":[0.9995192,0.00005923943,0.00009459466,0.0001757861,0.000131196,0.00001997997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00092496,0.0001034381,0.1449903,0.0003090588,0.0001174114,0.0008059293,0.001243444,0.09764075,0.1168437,0.0241592,0.0519047,0.5609571],"study_design_scores_gemma":[0.000236964,0.0002479404,0.285686,0.0002255574,0.00009053313,0.000747117,0.001149342,0.2471162,0.1573697,0.01414693,0.2927125,0.000271248],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6633345,0.0008595542,0.2218846,0.001131466,0.0005855993,0.0002680188,0.03617775,0.01167602,0.0640825],"genre_scores_gemma":[0.8730294,0.0002410024,0.1043919,0.0001756394,0.00008589091,0.0001159746,0.01660723,0.0004967892,0.004856265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01051002,"threshold_uncertainty_score":0.02089769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04123745430677531,"score_gpt":0.2249482511985195,"score_spread":0.1837107968917442,"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."}}