{"id":"W3216769419","doi":"10.1002/jrs.6281","title":"The Raman laser spectrometer ExoMars simulator (RLS Sim): A heavy‐duty Raman tool for ground testing on ExoMars","year":2021,"lang":"en","type":"article","venue":"Journal of Raman Spectroscopy","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"H2020 European Research Council; Secretaría de Estado de Investigación, Desarrollo e Innovación; Horizon 2020 Framework Programme; European Commission","keywords":"Spectrometer; Mars Exploration Program; Raman laser; Raman spectroscopy; Computer science; Laser; Remote sensing; Simulation; Exploration of Mars; Environmental science; Aerospace engineering; Optics; Physics; Geology; Engineering; Astrobiology; Raman scattering","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":[],"consensus_categories":[],"category_scores_codex":[0.0008144831,0.0002871871,0.0004231555,0.0001125049,0.0005863787,0.0005868536,0.0003942146,0.00005702801,0.0001013094],"category_scores_gemma":[0.0001249292,0.0002078509,0.0003177457,0.0003801852,0.0000829682,0.0006463251,0.00004482524,0.0004383487,0.0000699564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001207722,"about_ca_system_score_gemma":0.0002375791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001315385,"about_ca_topic_score_gemma":0.00001935601,"domain_scores_codex":[0.9976981,0.000112036,0.0006972124,0.0003300507,0.0005471633,0.0006154299],"domain_scores_gemma":[0.9978381,0.0007945324,0.0005485227,0.0003867423,0.0002565802,0.0001755187],"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":[0.006721651,0.003999111,0.1300123,0.0002224308,0.002783577,0.0009024833,0.00284693,0.03803965,0.5801978,0.03722574,0.1375506,0.05949777],"study_design_scores_gemma":[0.01872954,0.01450604,0.08128899,0.001042287,0.0009814862,0.0005133545,0.007914068,0.04508481,0.4978173,0.1776512,0.1505641,0.003906845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890973,0.00008736859,0.007000344,0.002052744,0.0007715667,0.0003140728,0.00003286699,0.00001980771,0.0006239022],"genre_scores_gemma":[0.9877988,0.00001512378,0.009434595,0.000475022,0.001727723,0.00001166283,0.00005558416,0.00003060035,0.0004509009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1404255,"threshold_uncertainty_score":0.8475912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193779103989989,"score_gpt":0.2699826170234613,"score_spread":0.2480448259835614,"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."}}