{"id":"W3094298137","doi":"10.5902/1983465955294","title":"Ranking product systems based on uncertain life cycle sustainability assessment: a stochastic multiple criteria decision analysis approach","year":2020,"lang":"en","type":"article","venue":"Revista de Administração da UFSM","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Vrije Universiteit Brussel; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Multiple-criteria decision analysis; Ranking (information retrieval); Robustness (evolution); Computer science; Decision analysis; Operations research; Decision support system; Product (mathematics); Data mining; Engineering; Machine learning; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01129626,0.0008056898,0.002006245,0.00108645,0.0006330783,0.004377749,0.002616741,0.0002602438,0.0006455833],"category_scores_gemma":[0.07817531,0.0006668467,0.0009100451,0.005953831,0.0002401287,0.0005458609,0.0004774912,0.0007383307,0.0001039425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007565845,"about_ca_system_score_gemma":0.001728946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006437226,"about_ca_topic_score_gemma":0.000007452723,"domain_scores_codex":[0.985989,0.002450213,0.002962769,0.003054152,0.004403033,0.001140822],"domain_scores_gemma":[0.9820703,0.01065946,0.001194417,0.003320263,0.001434967,0.001320548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006158522,0.001678809,0.02632051,0.0007859151,0.0007385351,0.0004059446,0.001769069,0.8919247,0.0008184879,0.003773984,0.004106046,0.06151949],"study_design_scores_gemma":[0.002167854,0.0003375786,0.0119327,0.0001263283,0.0003831954,0.000009913417,0.001678491,0.9781036,0.00001049384,0.0004187073,0.004133029,0.0006981363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2118689,0.0002922158,0.783426,0.001298997,0.0003908817,0.001793434,0.0002290071,0.0002281645,0.0004723998],"genre_scores_gemma":[0.9690452,0.000002495843,0.02949643,0.000647356,0.0003872118,0.0001860958,0.0001029388,0.00008052486,0.00005172436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7571763,"threshold_uncertainty_score":0.9995783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1519371297206755,"score_gpt":0.4420914335818273,"score_spread":0.2901543038611518,"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."}}