{"id":"W4387311720","doi":"10.1144/geochem2023-039","title":"Estimating the silica content and loss-on-ignition in the North American Soil Geochemical Landscapes datasets: a recursive inversion approach","year":2023,"lang":"en","type":"article","venue":"Geochemistry Exploration Environment Analysis","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Loss on ignition; Mineralogy; Amorphous solid; Analytical Chemistry (journal); Inversion (geology); Geology; Chemistry; Soil science; Environmental chemistry","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":[0.0009817634,0.0004958967,0.0003121596,0.001191718,0.0003970445,0.0006787194,0.001086311,0.0005647662,0.0004398748],"category_scores_gemma":[0.002419025,0.0003831325,0.0006356055,0.0007914757,0.0003314221,0.0005665303,0.0008260879,0.0007058703,0.0002947061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007097269,"about_ca_system_score_gemma":0.001244443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05361018,"about_ca_topic_score_gemma":0.1011273,"domain_scores_codex":[0.9996945,0.00006505432,0.00001884258,0.0001025504,0.00007938216,0.00003971862],"domain_scores_gemma":[0.9993761,0.0001492461,0.00008132768,0.0001272132,0.0002433237,0.00002275821],"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":[0.0003017287,0.0003454981,0.1335727,0.0001194789,0.000515804,0.0002193938,0.0004495395,0.5182922,0.04669634,0.002821525,0.006017179,0.2906485],"study_design_scores_gemma":[0.00003432046,0.00001948744,0.03452972,0.000007158425,0.00002455689,0.0000304613,0.00007453476,0.9580153,0.004807267,0.001092449,0.001341774,0.00002298298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7520021,0.0002066727,0.2373704,0.0003287784,0.00001559048,0.0001615896,0.003445333,0.004478805,0.001990788],"genre_scores_gemma":[0.7297679,0.00007136449,0.2608685,0.0001052,0.00001930342,0.0001631032,0.007812741,0.0002130191,0.0009788085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05361018,"threshold_uncertainty_score":0.1065962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290257955069534,"score_gpt":0.2192274080889531,"score_spread":0.1902016125819997,"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."}}