{"id":"W4385932451","doi":"10.1126/science.abn5962","title":"Extracting resources from abandoned mines","year":2023,"lang":"en","type":"article","venue":"Science","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mining engineering; Environmental science; Waste management; Geology; Engineering","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":[0.0003418219,0.00004875997,0.00004933858,0.0001020561,0.0001433407,0.00008483528,0.0001558378,0.00001632854,0.00005612788],"category_scores_gemma":[0.0001223713,0.0000405809,0.00001778324,0.0006151106,0.00005680969,0.0002500092,0.00002389065,0.00006345882,0.0002493739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001196173,"about_ca_system_score_gemma":0.000006301376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002731868,"about_ca_topic_score_gemma":0.00001433536,"domain_scores_codex":[0.9994355,0.000005664956,0.00008046244,0.0001255818,0.0001842127,0.0001685508],"domain_scores_gemma":[0.9997578,0.00006601607,0.00001289734,0.00009999966,0.00001154719,0.00005168622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001035688,0.00000200424,0.0006920677,0.000003504987,0.000001780538,0.000003918352,0.0004626271,0.001519579,0.965165,0.00002416239,0.000300341,0.03182402],"study_design_scores_gemma":[0.0002848938,0.00001562699,0.1763427,0.00007151298,0.000008515852,0.000009765515,0.001877158,0.3712482,0.2109321,0.0005096341,0.2382542,0.0004456985],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98816,0.00009800699,0.0002291802,0.00006241159,0.0006860984,0.00002317851,0.000001962764,0.000497161,0.01024196],"genre_scores_gemma":[0.9987614,0.00001749784,0.0005195494,0.00002208776,0.00011205,0.000001723,0.000001362343,0.000005198127,0.0005591506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7542329,"threshold_uncertainty_score":0.320528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750006760323763,"score_gpt":0.2460129917612397,"score_spread":0.228512924158002,"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."}}