{"id":"W2111890146","doi":"","title":"The Growth of Diamond Mining in Canada and Implications for Mining Productivity","year":2004,"lang":"en","type":"article","venue":"CSLS Research Reports","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diamond; Productivity; Production (economics); Value (mathematics); Investment (military); Mining industry; Agricultural economics; Business; Consumption (sociology); Natural resource economics; Economics; Demographic economics; Mining engineering; Engineering; Economic growth; Political science; Law; Mathematics; Metallurgy","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":[0.0012566,0.00005125409,0.00009981295,0.00006016506,0.00009277567,0.00002046565,0.00007493487,0.00002427443,5.888731e-7],"category_scores_gemma":[0.0006579745,0.0000451273,0.00001247184,0.0001311234,0.00005163956,0.00005624222,0.00004475791,0.0000947578,2.992245e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377772,"about_ca_system_score_gemma":0.0004486111,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1629129,"about_ca_topic_score_gemma":0.6010063,"domain_scores_codex":[0.9992602,0.00001042978,0.000237064,0.0001462248,0.00009168886,0.0002543915],"domain_scores_gemma":[0.9993439,0.0002154945,0.00003705051,0.0002567302,0.00009923057,0.00004759246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003505607,0.00006253295,0.8551159,0.000728591,0.00009361251,0.0001027983,0.003196851,0.00800983,0.01922932,0.006007853,0.02050945,0.08690819],"study_design_scores_gemma":[0.0006569907,0.0002089863,0.8084003,0.0003785974,0.00001380251,0.0003535394,0.001944353,0.006099248,0.1133573,0.05354488,0.01434482,0.0006971359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980918,0.0002456298,0.000244616,0.0003464946,0.00004850204,0.0002917283,0.000005317286,0.00001884721,0.0007071315],"genre_scores_gemma":[0.9970777,0.0001094256,0.002594871,0.000001847174,0.00002440284,0.0001561691,0.00000192728,0.00001332502,0.00002034443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4380934,"threshold_uncertainty_score":0.8426613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05275980907689377,"score_gpt":0.3068779243114005,"score_spread":0.2541181152345067,"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."}}