{"id":"W2975404461","doi":"10.1111/1365-2478.12882","title":"Petrophysics and mineral exploration: a workflow for data analysis and a new interpretation framework","year":2019,"lang":"en","type":"article","venue":"Geophysical Prospecting","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Geological Survey of Canada","funders":"Australian Society of Exploration Geophysicists Research Foundation","keywords":"Petrophysics; Geology; Categorical variable; Environmental geology; Mineral exploration; Workflow; Economic geology; Stratigraphy; Outcrop; Geophysics; Regional geology; Weathering; Petrology; Earth science; Geochemistry; Paleontology; Volcanism; Computer science; Porosity; Geotechnical engineering; Machine learning; Database","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":[0.0001757281,0.000163271,0.0003436345,0.00006594874,0.0001181883,0.0001777411,0.000175616,0.00006239508,0.00006908172],"category_scores_gemma":[0.0002943152,0.0001333187,0.00007549171,0.0008397204,0.00004200766,0.0005669336,0.0000589404,0.0002154454,0.00003984886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003207584,"about_ca_system_score_gemma":0.00002032225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009012749,"about_ca_topic_score_gemma":0.0001551694,"domain_scores_codex":[0.9986638,0.00005098671,0.0001976102,0.0006130078,0.0001801102,0.0002944947],"domain_scores_gemma":[0.9985579,0.000821355,0.00009242529,0.0003238643,0.00003948308,0.0001650243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001566329,0.00003405862,0.0839178,0.00005001948,0.0001751659,0.000001100163,0.0005530223,0.0006149138,0.000159634,0.002172184,0.00003908768,0.9121264],"study_design_scores_gemma":[0.000238393,0.0003079469,0.3134997,0.00001981377,0.0001865398,8.886154e-7,0.00005271881,0.510596,0.0000393828,0.1747291,0.0001284849,0.0002010964],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7786676,0.0001524056,0.2197993,0.0005837913,0.0001533372,0.0003750528,0.0000330467,0.0000530073,0.0001825146],"genre_scores_gemma":[0.8970819,0.000007399427,0.1018612,0.0001381049,0.000496354,0.00000300661,0.0001553898,0.000004797037,0.0002518355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9119253,"threshold_uncertainty_score":0.5436578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03492437884104815,"score_gpt":0.280152116475529,"score_spread":0.2452277376344809,"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."}}