{"id":"W2920515251","doi":"10.1139/cjes-2018-0177","title":"Up, down, or sideways: emplacement of magmatic Fe–Ni–Cu–PGE sulfide melts in large igneous provinces","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Earth Sciences","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Geology; Sill; Sulfide; Igneous rock; Lava; Geochemistry; Silicate; Volcano; Basalt; Mineralization (soil science); Dike; Partial melting; Volcanogenic massive sulfide ore deposit; Mineralogy; Chemistry; Materials science; Metallurgy; Pyrite","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000117465,0.000139817,0.0001375089,0.0005739048,0.0004248974,0.0004984891,0.0002975137,0.0002653376,0.001824391],"category_scores_gemma":[0.0004505084,0.0001895605,0.0002226181,0.0003895972,0.0003017744,0.0004340645,0.0005473697,0.0002076491,0.0003509038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000555762,"about_ca_system_score_gemma":0.0003607559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02552228,"about_ca_topic_score_gemma":0.0389034,"domain_scores_codex":[0.9999195,0.000004846768,0.000005428848,0.00002748556,0.00001470062,0.00002801551],"domain_scores_gemma":[0.9997893,0.00003136587,0.00006504808,0.00002766962,0.00004607641,0.00004052049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005154193,0.00003356779,0.8730403,0.00003875086,0.00003794229,0.001011834,0.001841574,0.0005317155,0.1024879,0.0002692938,0.0002758917,0.0199157],"study_design_scores_gemma":[0.000003088986,0.00002330686,0.9929889,0.000003101878,0.00001164134,0.0001549563,0.0005401546,0.0004769278,0.005268855,0.00004291217,0.000482411,0.000003878357],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984195,0.00002939182,0.00006339425,0.00001280848,0.000001390997,0.000001887653,0.00007423841,0.000008243434,0.001389037],"genre_scores_gemma":[0.9990145,0.00003638641,0.0002113049,0.000007839809,0.000002445393,0.000001402292,0.0001408393,0.000005119977,0.0005800596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02552228,"threshold_uncertainty_score":0.05074745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01515646230848441,"score_gpt":0.203877188206543,"score_spread":0.1887207258980586,"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."}}