{"id":"W1968417609","doi":"10.2514/6.2000-3111","title":"LANTR/ISPP-based space transportation for moon/Mars missions. I - Analysis","year":2000,"lang":"en","type":"article","venue":"36th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit","topic":"Spacecraft and Cryogenic Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Population and Public Health","keywords":"Mars Exploration Program; Astrobiology; Space exploration; Space (punctuation); Exploration of Mars; Computer science; Mars landing; Aerospace engineering; Remote sensing; Geology; Engineering; Physics; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005937367,0.0005845217,0.0002422874,0.001077664,0.0005943613,0.001203777,0.0007989032,0.000455781,0.01258641],"category_scores_gemma":[0.0007698793,0.0002440296,0.0006852481,0.001010842,0.0003327721,0.001510291,0.0005554378,0.000485212,0.00144074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003163171,"about_ca_system_score_gemma":0.001498979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0226699,"about_ca_topic_score_gemma":0.02124131,"domain_scores_codex":[0.9993805,0.0001151346,0.00001787762,0.00007331494,0.0003065982,0.0001065103],"domain_scores_gemma":[0.9996471,0.00005361881,0.00003159587,0.00002649412,0.0002251843,0.00001597563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004924423,0.0001928581,0.0188356,0.000342048,0.00008631993,0.0003299847,0.0000836722,0.8305386,0.0132797,0.03220971,0.0115862,0.09202284],"study_design_scores_gemma":[0.00002458253,0.0005473075,0.02248101,0.00003735755,0.00007297914,0.000183892,0.0003635304,0.9405465,0.01167007,0.006773887,0.01727064,0.00002826985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6194848,0.0008142036,0.1579388,0.0007625698,0.0001153136,0.000880642,0.008819704,0.001776288,0.2094076],"genre_scores_gemma":[0.959181,0.0003188539,0.01741142,0.00004868936,0.00001536779,0.0002376552,0.004612466,0.0001573007,0.01801732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0226699,"threshold_uncertainty_score":0.04507589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929995376042102,"score_gpt":0.2244203555806026,"score_spread":0.2051204018201816,"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."}}