{"id":"W2943491958","doi":"","title":"Chip off the new block: How blockchain could boost mineral supply chains","year":2019,"lang":"en","type":"article","venue":"Industrial Minerals","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blockchain; Business; Stock exchange; Commerce; Finance; Computer science; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002130503,0.0002626572,0.0002789768,0.0001051253,0.00008406519,0.0001818736,0.0002724273,0.0002981628,0.0007072822],"category_scores_gemma":[0.0001372425,0.0002001447,0.0001018927,0.0003335629,0.00003237559,0.0001487659,0.00002517247,0.0005260878,0.0002794365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004881881,"about_ca_system_score_gemma":0.0001122245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007904079,"about_ca_topic_score_gemma":0.0001364753,"domain_scores_codex":[0.9987473,0.00004938303,0.0003099072,0.0002317062,0.0002948624,0.0003668142],"domain_scores_gemma":[0.9992179,0.0001529957,0.00007825805,0.0003302026,0.00005812951,0.0001625303],"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":[0.00003061766,0.00002159074,0.0004746134,0.00001008367,0.00005471897,0.000003900666,0.0002739579,0.0146641,0.06781197,0.0006017523,0.9133765,0.002676265],"study_design_scores_gemma":[0.001434942,0.00006473371,0.000165532,0.00003053587,0.00002257791,0.00002435536,0.0001425223,0.01054065,0.00839902,0.00003723127,0.9788398,0.0002981592],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9165425,0.0007035676,0.00005762698,0.02028274,0.003548809,0.0008482658,0.00005676559,0.000482152,0.05747757],"genre_scores_gemma":[0.7038086,0.00003725988,0.00003038493,0.0004881882,0.002111285,0.00001965518,0.00002467092,0.00003722714,0.2934427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2359651,"threshold_uncertainty_score":0.8161665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106143251065762,"score_gpt":0.2429274292492705,"score_spread":0.2118659967386129,"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."}}