{"id":"W1487850528","doi":"10.1111/j.1477-9730.2011.00665.x","title":"Review of developments in geometric modelling for high resolution satellite pushbroom sensors","year":2012,"lang":"en","type":"article","venue":"The Photogrammetric Record","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada; Korea Aerospace Research Institute; University of Melbourne","keywords":"Photogrammetry; Satellite; Remote sensing; Computer science; Sensor fusion; High resolution; Computer vision; Artificial intelligence; Computer graphics (images); Geography; Aerospace engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00198059,0.0002829969,0.0004902071,0.001220749,0.00007625137,0.00003245031,0.0003381945,0.0001256412,0.00001999659],"category_scores_gemma":[0.0003520528,0.0002283589,0.0001514405,0.007032285,0.00004539794,0.0001858284,0.00003853486,0.0002906754,0.00002210548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001480858,"about_ca_system_score_gemma":0.00002539951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007532354,"about_ca_topic_score_gemma":0.00001170741,"domain_scores_codex":[0.997804,0.00008709502,0.0008147481,0.000226094,0.0002865308,0.0007815431],"domain_scores_gemma":[0.9985009,0.0006692168,0.0001766067,0.0003865097,0.0001383798,0.000128414],"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":[0.00004727902,0.0001228333,0.006050353,0.006197272,0.00008426805,6.390624e-7,0.0002297407,0.002355003,0.0003047212,0.00002594499,0.0005833815,0.9839985],"study_design_scores_gemma":[0.003272597,0.0003776444,0.01319244,0.01563787,0.0007207206,0.00008150726,0.0005175294,0.1579547,0.1201071,0.002004799,0.6827608,0.003372221],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1615651,0.575984,0.2553831,0.0000446343,0.001811977,0.002190372,0.00004048743,0.0003796411,0.002600755],"genre_scores_gemma":[0.8182312,0.1464642,0.03470827,0.0001363267,0.0001149703,0.0001731439,0.00004580818,0.00007119586,0.00005483157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9806263,"threshold_uncertainty_score":0.9312205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03442832250561409,"score_gpt":0.2565740537770619,"score_spread":0.2221457312714478,"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."}}