{"id":"W2497104813","doi":"10.1117/3.1002297.ch8","title":"User Acceptability Study of Satellite Data Compression","year":2013,"lang":"en","type":"book-chapter","venue":"Society of Photo-Optical Instrumentation Engineers eBooks","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Lossy compression; Lossless compression; Vector quantization; Data compression; Computer science; Hyperspectral imaging; Data compression ratio; Quantization (signal processing); Compression ratio; Image compression; Algorithm; Remote sensing; Artificial intelligence; Geography; Engineering; Image processing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003527639,0.0004955581,0.0007697963,0.0001174702,0.00008273935,0.00006365502,0.002648182,0.0003722795,0.0003159895],"category_scores_gemma":[0.00002598449,0.0004702143,0.0002423993,0.00005940791,0.0003276207,0.000755073,0.002151052,0.0005908607,0.00001236018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054806,"about_ca_system_score_gemma":0.00008952766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004519737,"about_ca_topic_score_gemma":0.000002800663,"domain_scores_codex":[0.9965212,0.00004828548,0.001153891,0.0009930484,0.0009891894,0.0002943337],"domain_scores_gemma":[0.9956189,0.0002600652,0.0006917294,0.002985489,0.0002699168,0.0001738308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009189134,0.001286955,0.0001701685,0.001394575,0.001260833,0.000006776195,0.008216616,0.0002253379,0.03295752,0.1599643,0.01609905,0.778326],"study_design_scores_gemma":[0.01320986,0.00511139,0.00355674,0.003008917,0.001086198,0.00003247278,0.009832569,0.1391491,0.5395862,0.08883773,0.1891477,0.007441127],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01311129,0.0003274262,0.8193227,0.0001024225,0.0009312304,0.006518515,0.0007529993,0.001185277,0.1577481],"genre_scores_gemma":[0.1468412,0.0002486788,0.8314373,0.0002012773,0.00009062016,0.000117358,0.0006238136,0.0001345253,0.02030521],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7708849,"threshold_uncertainty_score":0.9997749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03988409442465658,"score_gpt":0.2943121184179029,"score_spread":0.2544280239932464,"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."}}