{"id":"W6980416369","doi":"","title":"Canada's Strategy for Key Critical Raw Materials. Case Study: Copper and Graphite","year":2023,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Raw material; Production (economics); Resource (disambiguation); Graphite; Fuel supply","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":[0.001340871,0.000134883,0.0003502075,0.0002432451,0.0001609599,0.00005644575,0.0001274317,0.0001442879,0.0001421469],"category_scores_gemma":[0.001328593,0.0001162545,0.00003977496,0.0002781042,0.0004894052,0.00004084803,0.0001880046,0.0004443274,0.000004707836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002293791,"about_ca_system_score_gemma":0.0009540778,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05615141,"about_ca_topic_score_gemma":0.1096768,"domain_scores_codex":[0.9978741,0.00009960467,0.0003530033,0.0004812957,0.0003459228,0.000846014],"domain_scores_gemma":[0.9977697,0.001195482,0.0000166438,0.0003020832,0.0001280999,0.0005880143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004445465,0.002534911,0.04396751,0.003093773,0.0006798267,0.05221527,0.001214135,0.00002606756,0.102629,0.003361514,0.03085218,0.7549804],"study_design_scores_gemma":[0.05716268,0.01915698,0.237176,0.00157979,0.0003519297,0.01321142,0.1135638,0.01766219,0.05838152,0.01118678,0.4660259,0.004540942],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933746,0.00004096047,2.105286e-7,0.003517546,0.00007969554,0.000738707,0.0001025551,0.00002449189,0.002121235],"genre_scores_gemma":[0.9973194,0.0006755076,0.00003003017,0.0001849833,0.0001546933,0.0001977653,0.00004153952,0.00003011799,0.00136599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7504395,"threshold_uncertainty_score":0.9501337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05494516088545578,"score_gpt":0.3816615058139034,"score_spread":0.3267163449284476,"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."}}