{"id":"W2016328763","doi":"10.1180/minmag.2008.072.1.531","title":"Mapping singularities — a technique to identify potential Cu mineral deposits using sediment geochemical data, an example for Tibet, west China","year":2008,"lang":"en","type":"article","venue":"Mineralogical Magazine","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Geology; Mineral resource classification; Geochemistry; Mineral; Sediment; Heavy mineral; China; Mineral exploration; Mining engineering; Mineralogy; Geomorphology; Geography; Archaeology","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":[0.0003966572,0.0003193865,0.0002034662,0.001593362,0.0004153154,0.0003513262,0.0002987546,0.0001906718,0.0004728756],"category_scores_gemma":[0.000766662,0.0001026113,0.0001943059,0.001611709,0.0002991753,0.0003207313,0.0003812228,0.0001812355,0.00009603774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002186747,"about_ca_system_score_gemma":0.0003390334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007930574,"about_ca_topic_score_gemma":0.007966271,"domain_scores_codex":[0.999935,0.00001071707,0.000007319109,0.00001936496,0.00001669909,0.0000108955],"domain_scores_gemma":[0.9997332,0.000062402,0.00004810936,0.00003842327,0.00008538344,0.00003251048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007583125,0.000145173,0.2555067,0.0001861369,0.00009950268,0.006570328,0.001403559,0.05214901,0.1433841,0.005753057,0.002903915,0.5311403],"study_design_scores_gemma":[0.00008278733,0.0002354263,0.1572733,0.00002292078,0.0000918267,0.002249838,0.0009024285,0.787351,0.03922755,0.008560595,0.003954754,0.00004747882],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.900583,0.0001095987,0.09753676,0.000146618,0.000009837247,0.00003412032,0.0002070952,0.0003920513,0.0009808857],"genre_scores_gemma":[0.9350356,0.00005918029,0.06427025,0.000008737729,0.000004124483,0.000008928788,0.000179899,0.00001375321,0.0004195705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007930574,"threshold_uncertainty_score":0.01576883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07403514203857854,"score_gpt":0.2923659132725558,"score_spread":0.2183307712339773,"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."}}