{"id":"W2924737215","doi":"10.29173/ikc3916","title":"Kimberlitic olivine attrition: fingerprinting environments and timescales","year":2019,"lang":"en","type":"article","venue":"","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Attrition; Olivine; Geology; Computer science; Geochemistry","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":[0.0002238076,0.0002208128,0.0001609868,0.000860639,0.0004974946,0.0005896506,0.0003456011,0.0002888349,0.003357801],"category_scores_gemma":[0.0007896,0.0001411127,0.0001245075,0.0005823461,0.0002542468,0.0006726518,0.0003186861,0.0003209185,0.0004059422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002808516,"about_ca_system_score_gemma":0.0001678817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002689014,"about_ca_topic_score_gemma":0.004672147,"domain_scores_codex":[0.9998876,0.000004838753,0.00000450944,0.000046111,0.00002617602,0.00003075354],"domain_scores_gemma":[0.999685,0.00007583256,0.0001052047,0.00002676346,0.00007266678,0.00003448136],"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":[0.0007326429,0.0001007321,0.1035963,0.0001508427,0.0000473049,0.0002549455,0.0005556543,0.0007451284,0.8576226,0.0005122878,0.0003728992,0.03530862],"study_design_scores_gemma":[0.00001828159,0.0002991745,0.5388865,0.00004358312,0.00006684061,0.0006720632,0.0008785296,0.01161408,0.4385368,0.0004730675,0.008471779,0.00003931696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915113,0.0006740578,0.004537409,0.00005733814,0.00001174809,0.00001145646,0.0003865941,0.0001631828,0.002646976],"genre_scores_gemma":[0.9966492,0.0002071328,0.001443862,0.00001494259,0.000006770694,0.000008080356,0.0002499683,0.00005014999,0.001369889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003357801,"threshold_uncertainty_score":0.01123297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00339705601213974,"score_gpt":0.1592872017146725,"score_spread":0.1558901457025328,"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."}}