{"id":"W4387999324","doi":"10.56131/tmt.2023.2.2.175","title":"Electric cars in Lithuania – present and future","year":2023,"lang":"en","type":"article","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Electric cars; Promotion (chess); Battery (electricity); Electric vehicle; Battery electric vehicle; Automotive engineering; Transport engineering; Business; Engineering; Telecommunications; Political science; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000203414,0.0002824689,0.0001637642,0.001468195,0.0004644747,0.001544567,0.0002881481,0.0006055809,0.006682883],"category_scores_gemma":[0.0001519882,0.0001150751,0.0001918777,0.001682449,0.0003884423,0.001052944,0.0006021236,0.0003245865,0.0008981276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394217,"about_ca_system_score_gemma":0.001786879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005786676,"about_ca_topic_score_gemma":0.006034423,"domain_scores_codex":[0.9998611,0.00001899723,0.00001013419,0.00001900392,0.00003119286,0.00005951001],"domain_scores_gemma":[0.9998842,0.00002392487,0.00003369687,0.00000470955,0.00003161696,0.0000217912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002302045,0.0001529853,0.02168662,0.004525261,0.00004447538,0.002173288,0.001143953,0.002215541,0.003563606,0.07886981,0.03336833,0.852026],"study_design_scores_gemma":[0.000007626332,0.0002266299,0.09076837,0.002218396,0.00002898354,0.002637713,0.002955839,0.0004116171,0.0009101087,0.003807675,0.8959938,0.00003309064],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.07214006,0.8184549,0.0006584247,0.00925686,0.001190577,0.00001678003,0.000344441,0.0001059555,0.09783199],"genre_scores_gemma":[0.4361865,0.496141,0.001309522,0.001718037,0.001026375,0.00002126341,0.0005822742,0.00001808467,0.06299684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006682883,"threshold_uncertainty_score":0.02235645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003290949131693839,"score_gpt":0.184870470731241,"score_spread":0.1815795215995471,"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."}}