{"id":"W2907020151","doi":"","title":"Dust and ashes: : A picture of Liaoning's magnesia industry","year":2017,"lang":"en","type":"article","venue":"Industrial Minerals","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic shortage; Dynamite; Magnesium; Business; Agricultural economics; Quarter (Canadian coin); Engineering; Commerce; Natural resource economics; Geography; Metallurgy; Economics; Explosive material; Archaeology","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":[0.0005729045,0.0001297798,0.0002969953,0.00003049588,0.0006413997,0.0002153152,0.0004190816,0.0007172824,0.00029263],"category_scores_gemma":[0.0009523581,0.0001089717,0.00007058248,0.00004347655,0.0005591257,0.0004338896,0.0001013199,0.000485878,0.000007665604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007151538,"about_ca_system_score_gemma":0.0002603209,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01503348,"about_ca_topic_score_gemma":0.001781981,"domain_scores_codex":[0.9989809,0.00005534399,0.0002752577,0.0002206221,0.0001922248,0.0002756413],"domain_scores_gemma":[0.9989091,0.00007515529,0.0004823171,0.0003394781,0.00005047517,0.0001435015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001416572,0.0001278252,0.688593,0.00003179113,0.0001095078,0.00002987575,0.02037139,0.00001107479,0.001805078,0.03178218,0.1816002,0.07539646],"study_design_scores_gemma":[0.002289598,0.0001218355,0.1212635,0.0001546086,0.00004077657,0.00000362829,0.002654097,0.000007822668,0.0004567156,0.003668917,0.8689509,0.0003876392],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9077917,0.0000981621,7.48875e-7,0.004966572,0.000618519,0.0001965165,0.00002848363,0.00001654454,0.08628276],"genre_scores_gemma":[0.9509243,0.00004442405,0.00003852203,0.00009777377,0.001860612,0.000007448023,0.000001383128,0.000009891352,0.04701566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6873507,"threshold_uncertainty_score":0.9915255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05602359733867975,"score_gpt":0.3271619650634316,"score_spread":0.2711383677247519,"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."}}