{"id":"W4386170497","doi":"10.1016/j.actaastro.2023.08.032","title":"Statistical characterization of PIXL trace element detection limits","year":2023,"lang":"en","type":"article","venue":"Acta Astronautica","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"California Institute of Technology; National Aeronautics and Space Administration","keywords":"TRACE (psycholinguistics); Noise (video); Computer science; Trace element; SIGNAL (programming language); Data mining; Artificial intelligence; Geology","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":[0.0001126254,0.00007025465,0.00009171794,0.00005728292,0.00006328904,0.00001796764,0.00007106263,0.00001637524,0.0002175893],"category_scores_gemma":[0.00000565734,0.00006774063,0.00002131491,0.0002123222,0.00002845139,0.0002337501,0.00001345329,0.00005729841,0.000288809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008207786,"about_ca_system_score_gemma":0.00002530326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001231718,"about_ca_topic_score_gemma":0.000003046767,"domain_scores_codex":[0.9993254,0.00002431646,0.0001688884,0.0001375279,0.0001623873,0.0001814588],"domain_scores_gemma":[0.9997233,0.00003437513,0.00006652738,0.0001022193,0.00002523513,0.00004832881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000364121,0.00009810941,0.02049465,0.00001076664,0.00003148124,9.054298e-7,0.0003081746,0.0001526972,0.8495851,0.004325769,0.0003320832,0.1246239],"study_design_scores_gemma":[0.0004063137,0.0002821713,0.8773131,0.00001677132,0.00003912589,5.881068e-7,0.0003908548,0.0317494,0.07439639,0.001198568,0.01400543,0.0002012216],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457111,6.109465e-7,0.05328616,0.000291429,0.000120296,0.0001094109,0.0001519694,0.00003516145,0.0002938086],"genre_scores_gemma":[0.9978334,0.000001680607,0.0002632817,0.000009085326,0.00009004096,0.00001145414,0.001658524,0.00000523224,0.0001272859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8568185,"threshold_uncertainty_score":0.3712152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584271983108075,"score_gpt":0.2392392431561251,"score_spread":0.2233965233250443,"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."}}