{"id":"W3205429506","doi":"10.1016/j.eswa.2021.116060","title":"Anomaly detection for data accountability of Mars telemetry data","year":2021,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Mitacs; Polytechnique Montréal","keywords":"Telemetry; Mars Exploration Program; Anomaly detection; Computer science; Anomaly (physics); Remote sensing; South Atlantic Anomaly; Data mining; Geology; Telecommunications; Astrobiology","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":[0.0004322512,0.0001395053,0.0002245747,0.00007451328,0.0002670904,0.0001229918,0.00240133,0.0000830134,0.000006533336],"category_scores_gemma":[0.00003508422,0.0001270776,0.00003374882,0.0008899887,0.00006553605,0.0006835642,0.0007738537,0.00008353135,0.000008240319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004926101,"about_ca_system_score_gemma":0.0001821626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004094703,"about_ca_topic_score_gemma":0.0001539251,"domain_scores_codex":[0.9981402,0.00004471636,0.0004419746,0.0009560845,0.0002288133,0.0001881664],"domain_scores_gemma":[0.9928542,0.0001572896,0.0002586756,0.006254075,0.000399497,0.00007630249],"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":[0.0000960623,0.002568618,0.004767788,0.001032571,0.0005682595,0.000003826562,0.0008519337,0.0001984966,0.1599427,0.2153267,0.03813055,0.5765125],"study_design_scores_gemma":[0.0003748461,0.00008256357,0.0006996825,0.00003576915,0.00003045693,0.00009897449,0.0004667339,0.1460493,0.0400948,0.0004533933,0.8112494,0.0003640766],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005156141,0.0006843599,0.9959956,0.000306099,0.00007267139,0.001354173,0.0003847611,0.0002711669,0.000415589],"genre_scores_gemma":[0.7364277,0.00005039587,0.2597078,0.00007295183,0.0001673087,0.0028722,0.0005049665,0.00002045826,0.0001761496],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7731189,"threshold_uncertainty_score":0.5182072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06414976024322895,"score_gpt":0.3322822724052223,"score_spread":0.2681325121619934,"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."}}