{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007084331,0.00005574785,0.00005650831,0.00006210892,0.0002025584,0.00006343905,0.0001266492,0.00001060905,0.003380731],"category_scores_gemma":[0.00001385315,0.00005332467,0.00002123048,0.0002954136,0.000008688938,0.00008518254,0.00004915888,0.0000908396,0.0005084407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004225223,"about_ca_system_score_gemma":0.00001121065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008221121,"about_ca_topic_score_gemma":0.00006302347,"domain_scores_codex":[0.9994404,0.000009543311,0.00009600721,0.0001374612,0.0001918364,0.0001247128],"domain_scores_gemma":[0.9997588,0.00001513239,0.000009985226,0.0001314882,0.00001464668,0.00006989334],"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":[0.000008889654,0.00006912218,0.001231481,0.00001550453,0.0000183238,0.0000208699,0.001311914,0.03333484,0.03075374,0.001008801,0.9200354,0.01219115],"study_design_scores_gemma":[0.00006785679,0.000008775485,0.003786166,0.000001137922,0.000002381761,0.000002918148,0.0001255314,0.002663558,0.001360602,0.000191585,0.9917014,0.00008803478],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6930885,0.0006399826,0.1026927,0.002838417,0.021549,0.0004887179,0.001055244,0.002009485,0.1756379],"genre_scores_gemma":[0.9542544,0.000005407891,0.0005908961,0.0004606275,0.0001209937,0.0000580331,0.00007965678,0.00001407327,0.0444159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2611659,"threshold_uncertainty_score":0.9975303,"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."}}