{"id":"W2035421264","doi":"10.1109/tgrs.2012.2211605","title":"Stereo Radargrammetry With Radarsat-2 in the Canadian Arctic","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Canadian Space Agency","keywords":"Notation; Elevation (ballistics); Algorithm; Computer science; Remote sensing; Artificial intelligence; Mathematics; Geometry; Geography; Arithmetic","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":[0.0004723177,0.0004403863,0.0002299207,0.002045683,0.001493681,0.0009183541,0.0006043651,0.0002717478,0.002724894],"category_scores_gemma":[0.0006549775,0.0002684378,0.0003610897,0.004627477,0.0004166001,0.000497428,0.0004933517,0.0003738599,0.0006613176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009720403,"about_ca_system_score_gemma":0.01641057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9828585,"about_ca_topic_score_gemma":0.9911409,"domain_scores_codex":[0.9993481,0.00002709982,0.00001427118,0.0001231556,0.0003891554,0.00009814891],"domain_scores_gemma":[0.9996554,0.00001025279,0.00001294222,0.00002368988,0.0002714663,0.00002620343],"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":[0.0005715576,0.0002445027,0.08324835,0.000438274,0.0001479692,0.000891139,0.00192999,0.1563683,0.06196011,0.009472759,0.0425667,0.6421604],"study_design_scores_gemma":[0.0001462408,0.0001178312,0.5644181,0.0001769478,0.0001814236,0.0004325107,0.001990648,0.2409832,0.03128193,0.00170691,0.1582582,0.0003061294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7985184,0.001221369,0.06684196,0.0009545735,0.0001886168,0.0004909137,0.04192388,0.003278218,0.08658211],"genre_scores_gemma":[0.8777124,0.0009835017,0.08268639,0.0001253194,0.00002264543,0.00009028316,0.02099738,0.0002673018,0.0171149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01714146,"threshold_uncertainty_score":0.07052678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02146442295116022,"score_gpt":0.2124928430590281,"score_spread":0.1910284201078679,"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."}}