{"id":"W3136351189","doi":"10.5382/geo-and-mining-02","title":"Mineral Exploration: Discovering and Defining Ore Deposits","year":2019,"lang":"en","type":"article","venue":"SEG Discovery","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Mineral exploration; Variety (cybernetics); Mineral resource classification; Earth science; Geology; Drill; Mining engineering; Data science; Mining industry; Computer science; Engineering; Geochemistry; Artificial intelligence","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":[0.00009439592,0.0001112795,0.0001154704,0.0000253718,0.00007891573,0.0003091785,0.0002456568,0.00004290523,0.000008554492],"category_scores_gemma":[0.00002830131,0.00009783378,0.00003232713,0.0001328777,0.00002158787,0.001902776,0.0003139474,0.00008690305,0.00004393251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001120348,"about_ca_system_score_gemma":0.00002752754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001698681,"about_ca_topic_score_gemma":0.0000136728,"domain_scores_codex":[0.9992012,0.00001896281,0.0001235682,0.000325796,0.0001269796,0.0002034573],"domain_scores_gemma":[0.9995327,0.0000436891,0.00004957968,0.0003091273,0.00002054948,0.000044342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005895445,0.0001511579,0.3299401,0.0005687337,0.0001150233,0.000175212,0.0076558,0.01547279,0.08635657,0.5225204,0.002812494,0.03417275],"study_design_scores_gemma":[0.007030463,0.001185321,0.3566423,0.001724261,0.0001012381,0.001142543,0.009448302,0.2434069,0.1569315,0.1637632,0.0524895,0.006134518],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368492,0.0002311895,0.04184311,0.00144978,0.0003174011,0.00008716963,0.000001632566,0.00007831937,0.01914221],"genre_scores_gemma":[0.993219,0.00001226886,0.002957039,0.0001974423,0.00003717947,0.000006556068,0.000008290951,0.000002460625,0.003559747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3587573,"threshold_uncertainty_score":0.3989546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118376403947745,"score_gpt":0.2060863080582205,"score_spread":0.194902544018743,"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."}}