{"id":"W4400166382","doi":"10.1016/j.gexplo.2024.107539","title":"A comparison of PCA and ICA in geochemical pattern recognition of soil data: The case of Cyprus","year":2024,"lang":"en","type":"article","venue":"Journal of Geochemical Exploration","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Independent component analysis; Geology; Principal component analysis; Pattern recognition (psychology); Geochemistry; Soil science; Artificial intelligence; Computer science","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":[0.0007910794,0.00009718569,0.000315916,0.00009146526,0.00002016901,0.00003031016,0.0004164893,0.0001008161,0.00001090681],"category_scores_gemma":[0.0004806774,0.00007085592,0.00006064591,0.000311093,0.000117159,0.0006005247,0.0002441614,0.0003137919,6.761975e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001671727,"about_ca_system_score_gemma":0.00007596902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004992175,"about_ca_topic_score_gemma":0.00001966847,"domain_scores_codex":[0.9985663,0.00007717131,0.0008344555,0.0001896753,0.0002181421,0.0001143061],"domain_scores_gemma":[0.9985479,0.0003561245,0.0004681103,0.0003110019,0.0002710639,0.00004585978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001718743,0.0007263913,0.003270635,0.001403005,0.0001329506,0.0004667425,0.008315876,0.0006806153,0.7744779,0.0005517282,0.003362702,0.2064396],"study_design_scores_gemma":[0.0005249461,0.000219809,0.0001983725,0.0007230788,0.00005767463,0.001076937,0.001246756,0.2172066,0.7601076,0.01812818,0.0003669463,0.0001431227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660251,0.0007756983,0.02973348,0.00309101,0.000116891,0.00007363602,0.000018012,0.000007737493,0.0001584183],"genre_scores_gemma":[0.9980684,0.00008503139,0.001723277,0.00001772439,0.00007598857,0.000002083529,0.00002221161,0.000002039306,0.000003240824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.216526,"threshold_uncertainty_score":0.2889421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09120198717378264,"score_gpt":0.3242350007072307,"score_spread":0.233033013533448,"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."}}