{"id":"W4286327151","doi":"10.1144/geosci2022-003","title":"From dirt to pay dirt","year":2022,"lang":"en","type":"article","venue":"Geoscientist","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Lakehead University","keywords":"Dirt; Geography; Cartography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00120086,0.0007155454,0.0005878771,0.001030065,0.002881904,0.007751916,0.001331568,0.003499115,0.06738058],"category_scores_gemma":[0.004273857,0.0003592868,0.0004240616,0.001142161,0.004925915,0.008256298,0.00367181,0.004710822,0.03490921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002326774,"about_ca_system_score_gemma":0.00288978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003975336,"about_ca_topic_score_gemma":0.008318551,"domain_scores_codex":[0.9982679,0.0002210268,0.00005753162,0.0002969224,0.0009225017,0.0002340947],"domain_scores_gemma":[0.9984893,0.0002331272,0.00011468,0.0002130488,0.0006419619,0.0003080395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001099769,0.00007917963,0.001231564,0.0007682668,0.00002591593,0.0003063373,0.001155687,0.0002272317,0.00280008,0.2980056,0.4569596,0.2383305],"study_design_scores_gemma":[0.000003403451,0.0000346248,0.0002671998,0.0002783512,0.000005067511,0.0002214338,0.0006086618,0.00004947486,0.000838881,0.02553167,0.9721479,0.00001329576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01165665,0.05903903,0.01566031,0.1757779,0.02646313,0.00007167927,0.0008827592,0.0009436649,0.7095048],"genre_scores_gemma":[0.1573899,0.06267894,0.00935756,0.07865509,0.005049383,0.00008615106,0.001027961,0.001419855,0.6843351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06738058,"threshold_uncertainty_score":0.2254105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007739217200933583,"score_gpt":0.2275161469980982,"score_spread":0.2197769297971646,"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."}}