{"id":"W2041334995","doi":"10.1364/ao.45.003022","title":"Application of integrated sensing and processing decision trees for target detection and localization on digital mirror array imagery","year":2006,"lang":"en","type":"article","venue":"Applied Optics","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Hyperspectral imaging; Computer science; Hadamard transform; Computer vision; Data cube; Artificial intelligence; Image processing; Remote sensing; Digital image processing; Set (abstract data type); Suite; Data set; Data processing; Pattern recognition (psychology); Optics; Data mining; Geology; Image (mathematics); Physics","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":[0.0008550989,0.0004900115,0.0004364742,0.0004900568,0.0002569197,0.0004191561,0.0004440194,0.000303953,0.0007639115],"category_scores_gemma":[0.002272012,0.0001329205,0.0003692202,0.0005994839,0.0002592136,0.000455554,0.0004106827,0.0004758491,0.0001508919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003711704,"about_ca_system_score_gemma":0.0004675787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001636576,"about_ca_topic_score_gemma":0.001654391,"domain_scores_codex":[0.9995425,0.000152559,0.00002651925,0.0000703188,0.0001581431,0.00005000183],"domain_scores_gemma":[0.9991266,0.000481991,0.00007900922,0.00006853208,0.0001958888,0.00004792489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004039395,0.0001935263,0.003471998,0.0001103778,0.00009362963,0.000173366,0.0001446149,0.5182949,0.0375945,0.01134176,0.001540217,0.4266371],"study_design_scores_gemma":[0.000008523321,0.00005419228,0.000399679,0.000002534614,0.00001042375,0.00002709321,0.00001044502,0.988235,0.007269566,0.003584405,0.0003923552,0.000005860345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1177902,0.000116012,0.8800752,0.0001104976,0.00002176553,0.00005095499,0.0001028268,0.0004684228,0.00126413],"genre_scores_gemma":[0.6314791,0.00007430267,0.3673193,0.00004149184,0.00002346152,0.00009232427,0.0002085874,0.00003280369,0.0007285816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001636576,"threshold_uncertainty_score":0.004522264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00651941891569049,"score_gpt":0.206025895745138,"score_spread":0.1995064768294475,"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."}}