{"id":"W2113686302","doi":"10.1071/aseg2012ab160","title":"Geophysical Characteristics of the Carrapateena Iron-Oxide Copper-Gold Deposit","year":2012,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Teck (Canada)","funders":"","keywords":"Geology; Hematite; Petrophysics; Bedrock; Craton; Magnetic anomaly; Iron oxide copper gold ore deposits; Geochemistry; Copper; Magnetite; Gravity anomaly; Margin (machine learning); Geophysics; Mineralogy; Geomorphology; Paleontology; Tectonics; Hydrothermal circulation; Porosity; Materials science","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":[0.0002431612,0.0001944626,0.0002913974,0.00003132697,0.0001085763,0.00002537827,0.000335402,0.000102875,0.0001638474],"category_scores_gemma":[0.0001700436,0.0001207833,0.000170807,0.0002918915,0.000131159,0.0002464509,0.0000272805,0.0003327446,0.0003411229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005051296,"about_ca_system_score_gemma":0.0000315015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002086494,"about_ca_topic_score_gemma":0.00006312106,"domain_scores_codex":[0.9983056,0.0001345153,0.0003559297,0.0002131422,0.0003918083,0.0005990553],"domain_scores_gemma":[0.9987867,0.00035087,0.0001889279,0.0003367497,0.00004665196,0.0002901105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00005058919,0.0002574716,0.04291633,0.00004590443,0.00002685774,0.00000716039,0.00009903143,0.00007008425,0.00192114,0.0003840233,0.000337896,0.9538835],"study_design_scores_gemma":[0.0001268901,0.00007823057,0.9865966,0.00001558253,0.0000388859,0.00001204519,0.00001516148,0.0001224993,0.01076269,0.0008806011,0.001182346,0.000168436],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952967,0.0002468021,0.00001348811,0.0001768295,0.000466535,0.0001481355,0.0000677132,0.00003048043,0.003553318],"genre_scores_gemma":[0.9983278,0.00001961577,0.000685847,0.0002933591,0.0003351619,0.000001532119,0.0000297107,0.000005910193,0.0003010994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9537151,"threshold_uncertainty_score":0.4925402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01295611984620784,"score_gpt":0.2249256642931403,"score_spread":0.2119695444469324,"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."}}