{"id":"W4231909901","doi":"10.46427/gold2020.1279","title":"Potential Genomic Applications in the Mining Industry","year":2020,"lang":"en","type":"article","venue":"Goldschmidt Abstracts","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agnico Eagle (Canada)","funders":"","keywords":"Computer science; Data science; Mining industry; Engineering; Mining engineering","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":[0.0002691169,0.0001220042,0.00009988101,0.00003350209,0.00007335668,0.0000598661,0.0004876895,0.0003016655,0.00003561131],"category_scores_gemma":[0.000131185,0.00009154406,0.00006124907,0.0001419375,0.0001104825,0.00000426754,0.0001309327,0.0003540782,0.00008957686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008544762,"about_ca_system_score_gemma":0.0001132426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001633088,"about_ca_topic_score_gemma":0.00001714226,"domain_scores_codex":[0.9988644,0.00003602814,0.0003005704,0.0002226641,0.000256897,0.0003194224],"domain_scores_gemma":[0.9994352,0.00002015919,0.00007124864,0.0002552456,0.00003977324,0.0001783927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001979081,0.0004592447,0.01954066,0.0002660422,0.0001225269,0.00006493734,0.003590865,0.002026194,0.8844256,0.0001550001,0.0524322,0.0367188],"study_design_scores_gemma":[0.001572666,0.000605453,0.3799807,0.00002344221,0.00003792935,0.00003455893,0.007524432,0.0007715082,0.05429182,0.0001461682,0.5543654,0.0006459695],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904258,0.0001895805,0.0003345841,0.003233502,0.00005231094,0.0003097712,0.00001801308,0.000009342534,0.005427138],"genre_scores_gemma":[0.996675,0.00008996951,0.0005884839,0.001766978,0.00054437,0.00002969494,0.0001394253,0.00001103949,0.000155055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8301338,"threshold_uncertainty_score":0.3733059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158538642565832,"score_gpt":0.2758184271512831,"score_spread":0.2542330407256248,"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."}}