{"id":"W3124797348","doi":"10.1371/journal.pone.0171823","title":"Energy and institution size","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Per capita; Energy consumption; Institution; Consumption (sociology); Energy (signal processing); Scale (ratio); Relation (database); Econometrics; Simple (philosophy); Economics; Computer science; Biology; Statistics; Ecology; Physics; Mathematics; Demography; Social science; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001814458,0.0001188537,0.0003094616,0.001422208,0.0006756335,0.002706672,0.0005137591,0.0008578381,0.01013942],"category_scores_gemma":[0.0178694,0.0001404638,0.0002316661,0.001893144,0.002298041,0.004697048,0.002164313,0.0006864262,0.0008202498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480474,"about_ca_system_score_gemma":0.0008968757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002078081,"about_ca_topic_score_gemma":0.003056131,"domain_scores_codex":[0.9987764,0.0003699854,0.00007256701,0.0002283114,0.0002659497,0.0002868691],"domain_scores_gemma":[0.9765568,0.01002998,0.006345885,0.001672265,0.001667198,0.003727961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003839899,0.0002285885,0.4112214,0.0003672842,0.0003544149,0.0003937693,0.00243847,0.0101435,0.002370259,0.361069,0.01543044,0.1955989],"study_design_scores_gemma":[0.000105097,0.0001971046,0.6064383,0.0002873577,0.0001038469,0.0004554974,0.005945275,0.004495716,0.001564969,0.279578,0.1007504,0.00007850453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.848581,0.00650274,0.008971659,0.02413945,0.0002081701,0.00004855334,0.001300517,0.0001452089,0.1101028],"genre_scores_gemma":[0.9956025,0.0008504033,0.0006287463,0.0002779663,0.00009347004,0.00001205937,0.0001607692,0.0000155691,0.002358536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01013942,"threshold_uncertainty_score":0.03391981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2355931470436712,"score_gpt":0.3412425339121675,"score_spread":0.1056493868684963,"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."}}