{"id":"W6948132519","doi":"10.48610/a831967","title":"Database of resource inventories and national policy actions to accelerate supply of Energy Transition Minerals (ETMs)","year":2023,"lang":"en","type":"dataset","venue":"The University of Queensland","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resource (disambiguation); Key (lock); Energy supply; Transition (genetics); Energy (signal processing); Energy policy; Energy transition","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":[0.0008918704,0.001071671,0.001028489,0.003097754,0.0005796617,0.001907596,0.001697502,0.00145307,0.04083404],"category_scores_gemma":[0.004583497,0.0004988793,0.0009273068,0.008029503,0.000260563,0.001174242,0.00109449,0.00169104,0.03938959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001913872,"about_ca_system_score_gemma":0.003031653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04776515,"about_ca_topic_score_gemma":0.06047267,"domain_scores_codex":[0.9991398,0.0001248371,0.0001216762,0.0002264551,0.00025538,0.0001318523],"domain_scores_gemma":[0.9978987,0.0006779914,0.0002411291,0.0002622479,0.0007574006,0.0001625179],"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":[0.00003887426,0.00002187094,0.001652534,0.0004499065,0.0000274373,0.00002295417,0.00001902813,0.0005732338,0.00006693586,0.001161234,0.9936799,0.002285978],"study_design_scores_gemma":[0.0001150749,0.00001119543,0.007383637,0.0003110406,0.00002358937,0.00004484201,0.000100128,0.0007889775,0.0002297789,0.001293854,0.9896743,0.00002347774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001312598,0.00004565225,0.00004642271,0.00005138629,0.00001272489,0.000004360351,0.9989987,0.00007016944,0.0006392926],"genre_scores_gemma":[0.0004924907,0.00005924654,0.0001911125,0.00003224618,0.000003866902,0.00002982674,0.9987121,0.00001975019,0.0004594123],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04776515,"threshold_uncertainty_score":0.1366035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04288742984448266,"score_gpt":0.2720114054473474,"score_spread":0.2291239756028647,"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."}}