{"id":"W4239795068","doi":"10.5772/37681","title":"Demonstration of Hyperspectral Image Exploitation for Military Applications","year":2012,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Infrared Target Detection Methodologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Hyperspectral imaging; Image (mathematics); Remote sensing; Computer science; Computer vision; Environmental science; Artificial intelligence; Geology","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":[0.0001964737,0.0004860244,0.0001498535,0.0002673535,0.0001729269,0.0005058181,0.0004218608,0.0006060168,0.008097046],"category_scores_gemma":[0.0001281733,0.0001750707,0.0002510635,0.0003331502,0.0001511059,0.0006435792,0.0004327443,0.0007886456,0.0047839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001603407,"about_ca_system_score_gemma":0.0001588867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003564442,"about_ca_topic_score_gemma":0.0006976108,"domain_scores_codex":[0.9998544,0.00000954534,0.000002075606,0.00001868668,0.0001013377,0.00001398695],"domain_scores_gemma":[0.9999328,0.00001224068,0.000004530326,0.00001057285,0.00002782141,0.0000120556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006906001,0.0001094918,0.0002698008,0.000237737,0.00001172742,0.0002893221,0.00008295615,0.001586539,0.8339021,0.005045403,0.02153673,0.1368591],"study_design_scores_gemma":[0.00002500062,0.0003008409,0.003991052,0.0000698766,0.00001197522,0.001330138,0.00009676088,0.03189111,0.7085555,0.005057239,0.2486326,0.00003780786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1491896,0.008655004,0.3695554,0.003353136,0.001285144,0.0002342097,0.002318762,0.006696193,0.4587125],"genre_scores_gemma":[0.3501499,0.009035286,0.3584986,0.001039082,0.0002787612,0.0002374959,0.003475158,0.001045662,0.2762401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008097046,"threshold_uncertainty_score":0.02708733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04456802396017463,"score_gpt":0.2730756880332276,"score_spread":0.228507664073053,"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."}}