{"id":"W2267845806","doi":"10.3390/en9020072","title":"Visualization of International Energy Policy Research","year":2016,"lang":"en","type":"article","venue":"Energies","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Visualization; Context (archaeology); Management science; Data science; Scale (ratio); Energy policy; Computer science; Engineering; Renewable energy; Artificial intelligence","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005454567,0.0008604828,0.0004549783,0.01223533,0.001266923,0.008686306,0.0005987131,0.001009455,0.01812281],"category_scores_gemma":[0.01582267,0.0003126298,0.0008879234,0.01482255,0.001330107,0.004706351,0.004638474,0.001262498,0.002051531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002254883,"about_ca_system_score_gemma":0.003960222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003911846,"about_ca_topic_score_gemma":0.003430055,"domain_scores_codex":[0.9976323,0.00132201,0.0001719957,0.0001940141,0.0004982798,0.0001814601],"domain_scores_gemma":[0.9917455,0.00428351,0.0007586601,0.00120609,0.00162785,0.0003784127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000239479,0.00006298615,0.005544482,0.001630645,0.000120153,0.0004520273,0.01699443,0.0160711,0.003780109,0.6577517,0.0758222,0.2215306],"study_design_scores_gemma":[0.00005864473,0.00004763905,0.006762667,0.001467441,0.00008274911,0.0003305255,0.01046709,0.02068994,0.003011804,0.1843522,0.772651,0.00007842197],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07068143,0.01785559,0.2724729,0.02295338,0.002767564,0.0005456897,0.02295002,0.009667033,0.5801064],"genre_scores_gemma":[0.6516805,0.01475506,0.2873441,0.0009458507,0.0008451531,0.001194393,0.01258483,0.002367268,0.02828285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9877647,"threshold_uncertainty_score":0.06062686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01985171198923296,"score_gpt":0.3432789212808202,"score_spread":0.3234272092915872,"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."}}