{"id":"W4389561800","doi":"10.7185/gold2023.18246","title":"Working around microanalytical data gaps to make multiscale predictions- exploring the Bon Accord nickel mineral species","year":2023,"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 Ottawa","funders":"","keywords":"Nickel; Mineral; Computer science; Materials science; Environmental science; Metallurgy","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":[0.0002860125,0.0001857646,0.0001688411,0.0001649935,0.0002320146,0.0002640522,0.0005551662,0.00004657935,0.00004792451],"category_scores_gemma":[0.000113812,0.0001389616,0.00004641445,0.000764446,0.00003748096,0.0002417761,0.0003627038,0.0002662794,0.0002964804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005740396,"about_ca_system_score_gemma":0.00001105125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000440767,"about_ca_topic_score_gemma":0.0002220004,"domain_scores_codex":[0.998702,0.00001533886,0.0002701215,0.0003263972,0.0002231643,0.0004629427],"domain_scores_gemma":[0.9990346,0.0001744598,0.00001605941,0.0006424359,0.0000174551,0.0001149554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005516854,0.00008054105,0.03593714,0.0002947125,0.0003966183,0.00009343252,0.003741681,0.417051,0.04545949,0.002336294,0.4215683,0.07298572],"study_design_scores_gemma":[0.0002758483,0.00002296811,0.01856687,0.0002803968,0.0000652479,0.00002634302,0.002999171,0.7790768,0.001037419,0.0001619869,0.1969632,0.0005237767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685019,0.0001611867,0.01243869,0.001449615,0.002092968,0.0001891831,0.00002731374,0.001438084,0.01370103],"genre_scores_gemma":[0.9754605,0.00007601626,0.003054567,0.00009083049,0.001152613,0.00003672432,0.00006798872,0.00005219084,0.02000853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3620259,"threshold_uncertainty_score":0.5666689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1395609332267377,"score_gpt":0.2827270807302611,"score_spread":0.1431661475035235,"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."}}