{"id":"W2901683766","doi":"","title":"Higher Q1 NEV sales bode well for battery raw material demand","year":2018,"lang":"en","type":"article","venue":"Industrial Minerals","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); China; Electrification; Business; Electric vehicle; Agricultural economics; Agricultural science; Engineering; Commerce; Electricity; Economics; Environmental science; Geography; Electrical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001499484,0.0002192794,0.0002678391,0.00007145487,0.00009262594,0.0001050269,0.0001920171,0.0003557478,0.0009891293],"category_scores_gemma":[0.00003330941,0.0001913822,0.00008064987,0.0001307128,0.00004916869,0.0001417562,0.00002660406,0.0001933974,0.00009646584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000445903,"about_ca_system_score_gemma":0.00002120985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003900123,"about_ca_topic_score_gemma":0.00001082593,"domain_scores_codex":[0.9989119,0.0000318019,0.0003125913,0.0002052091,0.0001212611,0.0004172774],"domain_scores_gemma":[0.9995251,0.0000708435,0.00005975258,0.0002036667,0.00004641698,0.00009423963],"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":[0.0001211031,0.00000834685,0.0004395749,0.00001605082,0.00006753711,0.000002355096,0.00003231944,0.0006942037,0.160606,0.0001335947,0.8342582,0.003620743],"study_design_scores_gemma":[0.002273036,0.0002973254,0.000751487,0.00004661232,0.00005991434,0.000008815543,0.000006137236,0.002311677,0.1566213,0.000888524,0.8363189,0.0004163243],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874561,0.0000929715,0.0006426992,0.0003643818,0.004339342,0.0004356929,0.0001383278,0.0002510262,0.006279407],"genre_scores_gemma":[0.9774,0.00001513207,0.0005860277,0.0002338119,0.0164187,0.00003719039,0.00007471669,0.0000699118,0.005164517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01207936,"threshold_uncertainty_score":0.9999241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02414702369759211,"score_gpt":0.2311704504433107,"score_spread":0.2070234267457186,"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."}}