{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007032134,0.0004346175,0.0004397394,0.002977049,0.003700092,0.004887634,0.001278463,0.0008906221,0.006870416],"category_scores_gemma":[0.004683636,0.000274994,0.0008016878,0.008774433,0.001441582,0.001378507,0.001694047,0.001495134,0.0006235781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1249043,"about_ca_system_score_gemma":0.1183068,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9978206,"about_ca_topic_score_gemma":0.9979949,"domain_scores_codex":[0.9982997,0.00006225466,0.00003474302,0.0001067236,0.0006774396,0.0008192306],"domain_scores_gemma":[0.9956352,0.0002504296,0.0002799366,0.00004662888,0.002798616,0.0009891257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006114467,0.0002191782,0.6125219,0.0008096526,0.0003140487,0.00261882,0.004926065,0.03456897,0.002068122,0.08129956,0.09693185,0.1631105],"study_design_scores_gemma":[0.000054162,0.00008056256,0.8284672,0.0007432492,0.0001209355,0.0003773542,0.01739774,0.01833598,0.001179133,0.01110354,0.1219795,0.0001605629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.771399,0.01478093,0.001760138,0.05710695,0.0003598326,0.000110102,0.02691657,0.0002711767,0.1272953],"genre_scores_gemma":[0.966535,0.01050395,0.0008693485,0.0007457646,0.00002923888,0.00001626408,0.00297524,0.00004508254,0.01828012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1249043,"threshold_uncertainty_score":0.9062485,"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."}}