{"id":"W2601756134","doi":"10.4095/295694","title":"Practical aspects of compositional data analysis using regional geochemical survey data","year":2015,"lang":"en","type":"report","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Compositional data; Survey data collection; Computer science; Geology; Data science; Statistics; Mathematics","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":[0.05506016,0.0009944399,0.001417827,0.00519846,0.001709827,0.006683953,0.004234454,0.001698525,0.004674668],"category_scores_gemma":[0.2102105,0.001123667,0.001471421,0.007072656,0.003331952,0.005041213,0.004057329,0.002676519,0.002494563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00183017,"about_ca_system_score_gemma":0.005131997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01470178,"about_ca_topic_score_gemma":0.01538058,"domain_scores_codex":[0.9491191,0.03568756,0.002525228,0.00347957,0.008673354,0.0005150695],"domain_scores_gemma":[0.7744567,0.1775127,0.005679137,0.02687903,0.01464172,0.0008308266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004551149,0.0004584542,0.05069915,0.001284886,0.0004325362,0.001070971,0.005527703,0.08934098,0.01206113,0.1815774,0.01574122,0.6413506],"study_design_scores_gemma":[0.0001416552,0.0002296662,0.0169555,0.0004868619,0.00009626282,0.001079268,0.006131329,0.452649,0.01078042,0.4625023,0.04878758,0.0001601875],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01612904,0.000322404,0.9707987,0.003587205,0.0000641579,0.0004345428,0.001274135,0.001636325,0.005753492],"genre_scores_gemma":[0.08936957,0.0002849412,0.9072179,0.0002967518,0.0000934553,0.0002749257,0.001324315,0.0002588878,0.0008791371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05506016,"threshold_uncertainty_score":0.2911894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4921571400813749,"score_gpt":0.4333060790167709,"score_spread":0.05885106106460403,"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."}}