{"id":"W4248991745","doi":"10.31031/amms.2017.01.000502","title":"Metals from Ores: An Introduction","year":2017,"lang":"en","type":"article","venue":"Aspects in Mining & Mineral Science","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Library science; Engineering; Computer science","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":[0.000594875,0.000102272,0.0001223344,0.0001217896,0.0002967503,0.0003184545,0.0004894206,0.00003530035,0.0001319999],"category_scores_gemma":[0.0003909617,0.00008920263,0.00002108376,0.0001634344,0.0001884446,0.001274149,0.00005235159,0.0001490205,0.00002630082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006285192,"about_ca_system_score_gemma":0.00002096622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004124765,"about_ca_topic_score_gemma":0.0006248501,"domain_scores_codex":[0.9990398,0.00001709653,0.000156386,0.0003052831,0.0002305924,0.0002508809],"domain_scores_gemma":[0.9993706,0.00002118028,0.00005206271,0.0004446252,0.00002109396,0.00009040618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000005024911,0.00002553183,0.002932731,0.000004394613,0.000005792748,0.0000153705,0.0008456332,0.004398725,0.9406343,0.001983599,0.0003028404,0.04884613],"study_design_scores_gemma":[0.00073455,0.0001387363,0.5654156,0.0000775154,0.00002125085,0.00003277022,0.001490946,0.297663,0.1110017,0.002130046,0.02038854,0.0009053772],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851122,0.00004275783,0.0002718878,0.0002594983,0.001513356,0.00004490673,0.000001714671,0.00009254623,0.01266112],"genre_scores_gemma":[0.9927711,0.000007253698,0.006324949,0.00002654673,0.0006313238,0.000003091503,0.000002794282,0.000008401893,0.0002245663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8296325,"threshold_uncertainty_score":0.3637578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227273574441328,"score_gpt":0.2886468848631029,"score_spread":0.2659195274189701,"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."}}