{"id":"W2570317525","doi":"","title":"Design and expected performances ofL, M and N band AGPMs for EELT/METIS.","year":2014,"lang":"en","type":"article","venue":"","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; Geography; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005847268,0.0005779942,0.0004337954,0.0003696109,0.0004590868,0.0008852282,0.001316031,0.0009308388,0.003792861],"category_scores_gemma":[0.0006218831,0.0002348687,0.0002721307,0.0002214132,0.0002832748,0.0005725482,0.000397109,0.0003307967,0.002557908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001123558,"about_ca_system_score_gemma":0.0005778951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314929,"about_ca_topic_score_gemma":0.001740862,"domain_scores_codex":[0.9995574,0.00006454476,0.00001853794,0.0001031568,0.0001927563,0.00006340401],"domain_scores_gemma":[0.9995573,0.00004306526,0.00008374279,0.00004261447,0.0002250658,0.00004815185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000782448,0.0001694234,0.003553009,0.0007321365,0.00008837835,0.0002519161,0.0003418173,0.008579586,0.8841926,0.009688293,0.007899228,0.08372113],"study_design_scores_gemma":[0.0001322821,0.002284333,0.007453673,0.000145777,0.0001017002,0.001016136,0.0001725024,0.1241868,0.7811458,0.001488567,0.08179122,0.00008116419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3998986,0.003263617,0.5164781,0.001986976,0.000658686,0.00089381,0.001393575,0.008899259,0.06652727],"genre_scores_gemma":[0.8979218,0.0003523769,0.0866604,0.0002502339,0.0001054756,0.00025834,0.0004684643,0.0001465647,0.01383639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003792861,"threshold_uncertainty_score":0.01268834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095647573120941,"score_gpt":0.2285852403212753,"score_spread":0.1976287645900659,"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."}}