{"id":"W4406664193","doi":"10.3390/min15010095","title":"A Genetic Model for the Biggenden Gold-Bearing Fe Skarn Deposit, Queensland, Australia: Geology, Mineralogy, Isotope Geochemistry, and Fluid Inclusion Studies","year":2025,"lang":"en","type":"article","venue":"Minerals","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Geology; Geochemistry; Skarn; Isotope geochemistry; Fluid inclusions; Ore genesis; Inclusion (mineral); Genetic model; Stable isotope ratio; Isotope; Mineralogy; Chemistry; Hydrothermal circulation; Paleontology","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":[0.0004153318,0.0002733014,0.0003414763,0.00006271848,0.0005569208,0.00009481205,0.0008564071,0.0001770432,0.000005116285],"category_scores_gemma":[0.00027104,0.0001981073,0.00009538324,0.0002206256,0.0001895886,0.00009548195,0.002475961,0.0001743538,0.000002520473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003567517,"about_ca_system_score_gemma":0.00004887584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003579224,"about_ca_topic_score_gemma":0.0002350083,"domain_scores_codex":[0.9983566,0.00004704257,0.0003631091,0.000620933,0.0001361799,0.0004761092],"domain_scores_gemma":[0.998682,0.0003244145,0.0001004001,0.0006247811,0.0002000573,0.00006835825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007409015,0.0001287574,0.01254891,0.0008890493,0.0005665621,0.00005611496,0.004452241,0.02436504,0.8239723,0.006818686,0.1203425,0.005785776],"study_design_scores_gemma":[0.001177031,0.00006889892,0.002331859,0.0001221531,0.0001061974,0.0001102761,0.0001733531,0.9169723,0.0347008,0.0294433,0.01430432,0.0004894689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8429826,0.009965045,0.1141188,0.0285589,0.0003984608,0.0008366131,0.00001221618,0.0001641995,0.002963124],"genre_scores_gemma":[0.933814,0.0002417772,0.01421835,0.0007913786,0.0001107972,0.0001749365,0.000006624016,0.000004364757,0.05063778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8926073,"threshold_uncertainty_score":0.8078583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04130828574348606,"score_gpt":0.2946794037968473,"score_spread":0.2533711180533613,"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."}}