{"id":"W2534774326","doi":"10.1115/ipc2000-152","title":"High Resolution Satellite Imagery: From Spies to Pipeline Management","year":2000,"lang":"en","type":"article","venue":"","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Satellite; Remote sensing; Launched; Satellite imagery; Pipeline (software); Space Shuttle; Computer science; High resolution; Geography; Engineering; Aerospace engineering","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":[0.001251901,0.0008327775,0.0006159745,0.0028806,0.0004837257,0.002779668,0.00143154,0.0006359518,0.007928019],"category_scores_gemma":[0.002674003,0.0007263543,0.0003776107,0.003315331,0.0008234003,0.003826788,0.001596193,0.0008483148,0.007673234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007142247,"about_ca_system_score_gemma":0.0005923358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00311907,"about_ca_topic_score_gemma":0.002388369,"domain_scores_codex":[0.9990941,0.0001376012,0.00005011873,0.0001551201,0.0004928821,0.00007013239],"domain_scores_gemma":[0.998968,0.0001068874,0.00009824547,0.0004052195,0.0003492005,0.00007252558],"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":[0.0001468335,0.0000723815,0.001700814,0.0002095367,0.00003442579,0.0001318998,0.0002578268,0.01023338,0.008227713,0.01901986,0.05631479,0.9036506],"study_design_scores_gemma":[0.00004807011,0.0002708023,0.01269014,0.000300232,0.00008766929,0.0009728,0.001114381,0.1984217,0.04737055,0.1309608,0.6075526,0.0002102849],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01062476,0.004340514,0.9291751,0.001655673,0.000235632,0.0002671262,0.003289626,0.02005645,0.03035507],"genre_scores_gemma":[0.1523684,0.007721699,0.8029079,0.0005496185,0.0005781713,0.0002675193,0.009471096,0.003449161,0.02268638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007928019,"threshold_uncertainty_score":0.02652186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007040102358496228,"score_gpt":0.2079108256367259,"score_spread":0.2008707232782297,"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."}}