{"id":"W2757637095","doi":"10.6000/1929-6002.2017.06.02.1","title":"Additional External Costs Analysis and Environmental CBA","year":2017,"lang":"en","type":"article","venue":"Journal of Technology Innovations in Renewable Energy","topic":"Life Cycle Costing Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Risk analysis (engineering); Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003090887,0.0001244206,0.0003033078,0.003813122,0.000355144,0.0002692537,0.0005302187,0.0001431769,0.001524545],"category_scores_gemma":[0.0009333259,0.0001205029,0.00009053275,0.001518407,0.0002241878,0.001161277,0.0002680492,0.0002114107,0.000004969063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001076387,"about_ca_system_score_gemma":0.00002791819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009775672,"about_ca_topic_score_gemma":0.001026353,"domain_scores_codex":[0.998857,0.00000642556,0.0005414502,0.0001753332,0.0002423957,0.0001773866],"domain_scores_gemma":[0.9981216,0.00005769904,0.001251091,0.0003641401,0.0001955116,0.000009934155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004257293,0.0003928985,0.872271,0.00001197964,0.0009995472,0.0001910508,0.000005728262,0.008470762,0.005360303,0.02453053,0.04470068,0.04302293],"study_design_scores_gemma":[0.002890396,0.00008444229,0.5195196,0.0004358081,0.001451256,0.0002152441,0.0008156634,0.03750053,0.003226015,0.0715485,0.3613363,0.0009762471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775696,0.0003483477,0.00933155,0.00500118,0.000332717,0.00005094228,0.0001604568,0.00006527494,0.007139867],"genre_scores_gemma":[0.9956117,0.00003270784,0.003076154,0.000343541,0.0003672946,0.000009948984,0.0001085953,0.00001116662,0.0004389533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3527514,"threshold_uncertainty_score":0.9993882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00925638919237745,"score_gpt":0.2239019931414467,"score_spread":0.2146456039490693,"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."}}