{"id":"W4296997579","doi":"10.5194/epsc2022-835","title":"Miniature LIDAR for Mars Exploration","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Mars Exploration Program; Lidar; Astrobiology; Remote sensing; Exploration of Mars; Mars landing; Environmental science; Geology; Aerospace engineering; Engineering; Physics","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":[0.000622101,0.000749073,0.0003944118,0.0009366826,0.000459026,0.001160265,0.001456952,0.001557158,0.05738857],"category_scores_gemma":[0.0009769845,0.0002214692,0.0003094716,0.0008806739,0.0003514703,0.002025492,0.00171703,0.001503544,0.02731831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005901786,"about_ca_system_score_gemma":0.0003514309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003951696,"about_ca_topic_score_gemma":0.0004723902,"domain_scores_codex":[0.9993505,0.00008950791,0.00001797607,0.0001295974,0.0003624644,0.00004984432],"domain_scores_gemma":[0.9995092,0.00005593103,0.00004080385,0.00008116339,0.0002662349,0.00004669573],"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":[0.0001888621,0.00007878864,0.0008373029,0.0004160957,0.00001914995,0.0003051976,0.0001886526,0.001969827,0.1135922,0.03045077,0.1969245,0.6550286],"study_design_scores_gemma":[0.00003370871,0.0002421497,0.001012442,0.0001363732,0.00002048205,0.0006836017,0.000128183,0.01409781,0.02368799,0.008765778,0.951143,0.0000484815],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01846173,0.01192439,0.5086478,0.01139389,0.005521298,0.0007680063,0.004199789,0.01665178,0.4224312],"genre_scores_gemma":[0.2679421,0.005954972,0.4564297,0.005850859,0.00314447,0.0006763133,0.004448327,0.001201532,0.2543518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05738857,"threshold_uncertainty_score":0.1919839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03341690466303586,"score_gpt":0.2616918335971863,"score_spread":0.2282749289341504,"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."}}