{"id":"W2616548057","doi":"","title":"Section 3. Mineral Exploration: Discovering and Defining Ore Bodies","year":2017,"lang":"en","type":"article","venue":"Geochemical Perspectives","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Section (typography); Mineral exploration; Mineral; Mining engineering; Value (mathematics); Geology; Archaeology; Geochemistry; Geography; Computer science; Metallurgy; Materials science; Machine learning","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":[0.0001042048,0.0001230052,0.0001251674,0.00002322647,0.0005667785,0.000388425,0.0003699822,0.00006779259,0.00001379249],"category_scores_gemma":[0.0004817061,0.0001133818,0.00003957096,0.00003122026,0.0001801135,0.001010253,0.0004438947,0.0001504845,0.000005794512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002721239,"about_ca_system_score_gemma":0.0000158711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004268628,"about_ca_topic_score_gemma":0.00001147801,"domain_scores_codex":[0.9991552,0.00001311884,0.0001017142,0.0004118347,0.0001136322,0.0002044591],"domain_scores_gemma":[0.9992863,0.00003902373,0.00008765215,0.0004427055,0.00008190592,0.00006240058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009023632,0.0002739598,0.05138439,0.0002252533,0.0001774063,0.0001119766,0.08367454,0.0004010245,0.3884808,0.449748,0.006775958,0.01865642],"study_design_scores_gemma":[0.00313094,0.0003646917,0.1478741,0.0004331307,0.00006520838,0.0005009076,0.04343621,0.05458228,0.2205486,0.4967586,0.02944291,0.002862427],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8803439,0.0008246519,0.01936536,0.01821641,0.0003569095,0.000110695,0.000003295702,0.0002405526,0.08053819],"genre_scores_gemma":[0.9940029,0.0000391692,0.004971745,0.00002886616,0.0001720769,0.00001262886,0.00000258125,0.00000199239,0.000768059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1679322,"threshold_uncertainty_score":0.4623575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02184591383690034,"score_gpt":0.252665282572747,"score_spread":0.2308193687358466,"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."}}