{"id":"W2591177475","doi":"10.1071/aseg2009ab091","title":"Deep exploration technologies for illuminating highly prospective ground in the shadow of headframes","year":2009,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geoscience BC","funders":"","keywords":"Brownfield; Emerging technologies; Computer science; Remote sensing; Geology; Engineering; Civil engineering; Artificial intelligence; Redevelopment","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00029067,0.00037242,0.0001826954,0.000627409,0.0002604768,0.000930052,0.0003363608,0.000352947,0.004246659],"category_scores_gemma":[0.0003595229,0.0001704765,0.0001171372,0.0007634723,0.0004219579,0.0009097595,0.0009975435,0.0003339744,0.001182229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003474278,"about_ca_system_score_gemma":0.0005261041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001013642,"about_ca_topic_score_gemma":0.003984067,"domain_scores_codex":[0.999729,0.00004226293,0.000006883165,0.00002876156,0.0001647008,0.00002833505],"domain_scores_gemma":[0.999779,0.00006360244,0.00002772793,0.00003100675,0.00007868569,0.00001988644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009104898,0.00003682625,0.005296071,0.0005904839,0.00002091542,0.000378006,0.000861886,0.004008377,0.3271809,0.02836613,0.01046882,0.6227005],"study_design_scores_gemma":[0.00005400783,0.0007863989,0.02458498,0.0003179491,0.0001044191,0.004925082,0.003535538,0.03133428,0.2956496,0.03313955,0.6054496,0.0001186695],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1411361,0.01550123,0.7408789,0.002389686,0.0003970215,0.0001836848,0.0004056324,0.002100226,0.0970074],"genre_scores_gemma":[0.5459142,0.0119129,0.3836887,0.000619432,0.0001863519,0.0001129026,0.0003657128,0.0001238897,0.05707593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004246659,"threshold_uncertainty_score":0.01420647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788155148233679,"score_gpt":0.2777085074137493,"score_spread":0.2598269559314125,"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."}}